Sometimes you need to upload a file into your Posit Cloud workspace. Here I want to upload a copy of the remixed RMD file because I accidentally deleted that file and needed to replace it. To upload, the first thing you want to do is navigate to the folder that you want to be in. Here the project folder, the root folder, is where we would put these RMD worksheets. If you wanted to upload an image file or a data file, I would first click on those folders and open up those. Once you're in the folder where you want the uploaded file to go, just click on the upload tab and then navigate to the location where the file was stored. And here it's in my downloads on my PC. That's the file right there, the remix. I just select that, click open, and it gives you some message there, and click OK. Now if I scroll down there a little bit, you can see I've got the remix file and I can just click on that, excuse me, click on that name and it will open up over here so I can edit it. If you want to export a file, it's just the opposite process. Click on the name of the file and go up here to the blue gear icon, which is the more file commands, click on that, and then click on export. And it gives you the name of the file that you're going to export. I know this doesn't delete the file, it just sends a copy down and you can edit the name right here if you wanted to change it a little bit. But I'm just going to leave it at that and I want to click download. And now that file has downloaded to wherever you sent it and you can see the original file is still there. So I hope this is helpful, how to upload and download files into Posit Cloud.


Medical images analysis has to scale, so let's automate it. Hi, my name is Guillaume Moutier. I am a technical evangelist at Red Hat in the storage business unit. So what are we trying to achieve? What is our problem? Let's say we are at an hospital and we have X-ray images to review. Well, of course, an AIML model can definitely help. But how can we efficiently analyze the images as they come in? For a continuous flow of thousands of images? How can we continuously retrend a model and redeploy it seamlessly? And at various locations simultaneously? Well, my answer to that is to use cloud-native architecture and patterns. In this demo, we will use bucket notifications with Red Hat self-storage, Kafka topics with the MQ streams, KDTive eventing and KDTive serving with OpenShift serverless, and finally Tecton CD with OpenShift pipelines. So here is the workflow of the demo. Imagine we are at an hospital, that's a rage location.  This will automatically trigger a notification and this message will be sent to a Kafka topic. Using KDTive eventing with a subscriber to this topic, KDTive serving will launch one or many parts depending on the load. Those parts will run an inference model to assess the risk of pneumonia. The result will be written on the image and a notification will be sent to a doctor. But if the model is not really sure of its assessment, let's say under 80% of certainty, a copy of the image will also be anonymized, removing the personal information that are printed on it and sent to a central data science lab. Here the image can be reviewed and classified by specialists and the model can be retrained using the same automated pattern. Once the new model has been generated, it is pushed to a Git repo, which will trigger a rebuild of the risk assessment container image that will automatically be deployed seamlessly. Of course, this risk assessment pipeline can be reproduced at many other locations at the edge, each one benefiting from this shared model training. Let's go see its running. First, let's take a look at my OpenShift environment. In my project, I have an image generator, which will generate this flow of images that are sent to our SAV bucket. I have a Kafka topic subscriber that's part of KDTive eventing, and I have my KDTive serving risk assessment service. For this demo, I've merged the two functions of the risk assessment of the anonymization of the image. That's for the sake of this demo. I have also in my project a deployment of Grafana, where I will have this dashboard where we will be able to monitor this flow. We'll see it in a moment. I have also some helpers, a database where I will record all the events happening, so all the images coming in, processed and anonymized. I have a small helper here in the image server that will allow us to see those live images coming into Grafana. Here is our Grafana dashboard. Let me launch the model. I will just patch the image generator to tell him to send a new image into the bucket every second. Now that the process has started, let me give you a quick tour of this dashboard. Here, of course, you can see the pipeline live with the number of images that are uploaded. The number of images that are processed and eventually the number of images that are anonymized. That's when the model again is unsure of its certainty. We have here a panel with the CPU and RAM usage. A panel with the number of containers that the risk assessment pods are running and the number of deployments it uses. You see it has some slight delay in displaying the result, but we can see here that we have one replica of the risk assessment pod, which contains two containers. We have also here a panel that gives the risk distribution for the model with the normal pneumonia or unsure assessment and the number of images that are processed by model version. Here it's pretty much straightforward with the list of the last 10 uploaded images, the last 10 processed images, and the last 10 anonymized images. Of course, you can see that there are less anonymized images than the total of uploaded or processed. This is also what we can see here on the risk distribution because the model that we are using here is relatively good with an 85% of certainty. It works well. Finally, we have here on this panel a display of the last uploaded, the last processed, and the last anonymized image. As it's quite difficult to see here what's happening, I have another panel where we can see those images at a greater scale. It's not so easy to see. Let's wait for images that are better. Let's do this with this one. Here you have the kind of images that are uploaded. A pure X-ray image with some personal information here at the bottom left that gives the name and date of birth and other information. Here that's how we process the image. What we do, we make a risk assessment here and we print it on top of the image. That's what it's printed here, unsure with a risk of 72%. We are unsure because it's less than 80% of certainty. But we still have this personal information written here in the bottom. What we do in the process is that we anonymized the images by blurring here this part where the personal information are. If we go back to our main panel, we will see also that we change the name of the images themselves. We remove the names that are here and the date of birth that is here. We generate some UID that can be linked to the patient file at the hospital. You see our process is going well, but I will try to put some more pressure on it by sending 10 images per second and we'll see how it scales. What I will do at the same time is also change the version of the model we use. Let's say we have received those images at our data science lab and we have trained a new model. This model now will be pushed to a repo which will trigger a change of model that is used here in our pipeline. Let's do this. We can see now that as we have increased the rate of images that are produced, the risk distribution, we can see that the number of images that are processed is growing up much faster. To face this new workload, we have now two deployments of our risk assessment pod to be able to handle this load. At the same time, we can see that we have switched models. Now we are using the version 2 model to process our images. We could also increase this rate many more times or we could put it down to zero and those pods will just go down to zero and our resources consumption would go to zero. That's how Knetif serving works. You can see that so far we have processed hundreds of images. This could be thousands. The whole pipeline we scale accordingly. We have also made a change in the model that we are using and we can see that there was no involvement of any team to be able to redo this pipeline. Everything has been fully automated. That's exactly how you can scale your data pipelines for data science, for example. I hope you have liked this demo. If you want to try it or learn how it's done, head out to my GitHub repo where you will find detailed walkthrough, detailed instructions on how to set up the different elements to be able to reproduce this demo yourself. Of course, you will find all the code that I'm using to make this. Thank you for your attention and have a great summit with Red Hat. Take care.


Hi, I am Dapushpa from Indian Institute of Technology, Kharagpur. Today I will be presenting our one compact adaptive DCQ review for attribute weighted sums from Kaling. This is a joint work with Kothistathu from Entity Research. And this work is done during my internship at Entity Research. In the functional encryption scheme, there is a set of authority who generates master's secret key and a master's public key. Using master public key and encryptor encrypts the message in and generates a cyber-tech CT. The decryptor who wants to decrypt the cyber-tech CT, where is a functional secret key SKF corresponding to the functional to the central authority. The central authority will generate a secret key SKF and gives it to the decryptor. Having a SKF, the decryptor can now decrypt the cyber-tech CT and launch function of the message in. The security of functional encryption scheme is defined in two models. First one is indistinguishable security model. In indistinguishable security or functional encryption, the adversary submits two pair of challenge messages M0, M1 in the challenge space. It cannot distinguish between encryption of M0 and the encryption of M1, given the fact that all the functional secret keys SKFI corresponding to the function FI that adversary has squared it satisfies the fact that FI of M0 equal to FI of M1. Adversary can query multiple number of six such secret keys. If the number of secret keys is priori bounded, then we call the scheme bounded collision resistance. And if the adversary is allowed to submit any polynomial number of secret key queries, then we call the scheme unbounded collision resistance. Simulation security of functional encryption is defined by two worlds. First one is the real work, where the challenger runs all the algorithms honestly. Second one is the ideal work, where the challenger runs the signature version of the algorithms. The adversary submits the single challenge message during the challenge space. The challenger will now compute the challenge server text using the challenge message M in the real world. And in the ideal world, it uses the functional values of the message M for all the functions that adversary has squared it for the security till now. For the post-challenge secret key queries, the challenger can use the functional values directly during the key generation process. The adversary will not be able to distinguish between the real and the ideal world. The simulation security captures the fact that the adversary can learn only the functional values from the challenge ciphertext for all the functions that it has a secret key. Both indistinguishability and simulation security are further classified into selective, semi-adaptive and adaptive security notions. I will discuss those notions in simulation security setting. In selective simulation security, the adversary will submit the challenge message M before seeing any public parameter. It can also query for many functional secret keys. The adversary should not be able to distinguish between the real and the ideal world. In semi-adaptive case, the adversary can see the master public key before choosing the challenge message M. In adaptive simulation security, the adversary is allowed to query some functional secret keys before choosing the challenge message. It can also query for some functional secret keys after seeing the challenge ciphertext. What we can see now that selective security is seems to be weaker than semi-adaptive security and semi-adaptive security is weaker than adaptive security. And in all such cases, simulation security implies indistinguishability security. In this paper, we construct functional encryption scheme for attribute related some functionality introduced by AGW20. In this functionality, the message M consists of two parts. First one is the public part, which is Excel. And the second one is the secret part, which is JDI. During decryption, the decryptor will learn the function of the message M, which is as follows. Summation over I, FXI transpose JDI. If I is not a private bounded, then you call the scheme a non-exploit scheme. To get an idea about the significance of the functionality, I will discuss some special cases. Firstly, if F outputs a fixed factor, then this functionality will imply inner product function encryption. Secondly, if J is payload and F is a Boolean function, then this functionality will give you attribute-based encryption. Lastly, if FX is of the form Y times GXY, where Y is a fixed factor and G is a Boolean function, then this functionality will imply attribute-based IPA-free, recently introduced in AGW20. There are some interesting applications of this functionality. I will discuss one of them. Suppose in a banking sector, all the employees are divided into certain categories. Job, JI, age, AI, experience, AI, salary, GI. Now let's say we want to compute the various salary of a certain group of people. Where JI is cashier, AI is greater than 40, and AI is equal to 10. That means the job is cashier, age is greater than 40, and experience is of various. Then using the attributed some functionality, we can calculate the average. By calculating summation of I, F of JI, AI, AI times GI, where XI is equal to JI, AI, AI, which are public part of the message, and GI, which is salary, is the secret part of the message. AGW20 proposed functional encryption schemes for attribute-weighted some functionality, with some interesting features. First one is that their scheme supports unbounded slots for weight functions, which are arithmetic branch important. The sci-fi text search depends only on the private part of the message, and the security is based on the KLEE node entity assumption, which are known to be standard assumptions. However, the security is based on only semi-adaptive simulation security. That means the scheme would not provide adaptive simulation security. As it seems that selective security is weaker than semi-adaptive security, however due to GKW, 16 selective security is equivalent to semi-adaptive security. Although existing transformations from semi-adaptive to adaptive security requires much more expressive functionality. This means that the underlying semi-adaptive secure functional encryption scheme should support general circuits. Therefore AGW20 proposed an open problem in their paper, how to construct a fee for attribute-weighted some with unbounded slots for AVP, having compact safer text, and adaptive simulation security based on standard assumptions. Now I will present some previous works and challenges in solving the proposed open problem. The left hand side of the screen, we have shown some ABEs presented in the context of partially attribute-weighted AGE 17 proposed ABE for general policies with semi-adaptive simulation security. ABE 17 proposed a much more efficient ABE for AVP policies with semi-adaptive simulation security, whereas DEUT 18 proposed ABE for AVP policies with adaptive simulation security. In the right hand side of the screen, we see some functional encryption schemes for different functionality. Starting from ACGU 20, where they proposed an attribute-based inner product functional encryption schemes where the policies are in certain circuits. The security is based on a distinguished duty-based adaptive model. AGW20 proposed ABE for attribute-weighted some functionality where the weight functions are arithmetic branching programs and the security is modeled as semi-adaptive simulation security. Their scheme also supports unbounded slot. AGW20 proposed ABE for quadratic functions with semi-adaptive simulation security. Lastly, AGW20 proposed ABE for inner product functional encryption with unbounded collision and adaptive simulation security. So, what we can see is that achieving unbounded collision with adaptive simulation security for function encryption is really a challenging task and till now we know it only for inner product functionality. In this work, we build ABE for attribute-weighted some functionality where the weight functions are AVP and we propose a scheme in adaptive simulation security. First, we propose a one-slot scheme, then we extend it to unbounded slot scheme with a small caveat, which I will extend the next slide. Our scheme supports compact cybertext, which means that the cybertext science will not grow with multiple occurrence of a particular attribute in the weight function. Our scheme is based on K-LIN assumption, which is a standard assumption and it basically generalizes the framework given by LN20 from ABE to FE, that means from a load-hiding to partial attribute-hiding setting. Also, we extend the industry we shoot the security of LN20 to simulation-based security for our FE. I will first keep the overview of our function encryption scheme before discussing our main construction. So, we require two cryptographic tools. First one is information theoretic tool, arithmetic key, carveling scheme, and short AKGS, which is a particular type of randomized encoding. And the second one is a computational tool, which is function-hiding inner product functional encryption in short IPFE. Using AKGS and IPFE, we first construct a one key one cybertext secure one-slot FE scheme in the security setting. Then we extend it to a one-slot FE scheme in the public key setting. However, for that we require a slotted version of the IPFE. I will discuss about the slotted IPFE in a bit. Then we extend our one-slot one FE scheme into a one-slot one EXTFE scheme, which is again in the security setting, and it supports one key and one cybertext. So, what is the EXTFE functionality? The secret key is generated for a function and a vector Y. And the cyber fix is generated for a vector X, which is public and a vector Z, concatenated with a vector W, which are secret. The decryption will recover from effects transpose Z plus Y transpose dark blue. Then we extend this one-slot one EXTFE scheme to a full-fledged one-slot EXTFE scheme, using the same idea that would be involved in the assumption of one-slot one FE to one-slot FE scheme. That means we require slotted IPFE. After that, we use the assumption given by AGW20 with a little modification to get our unbounded-slot FE scheme in adaptive simulation with security. Here, I would like to mention one thing is that in our one-slot FE scheme, adversary can query any polynomial number of secret keys both before and after the challenge cybertext. Whereas, in our unbounded-slot scheme, adversary can query a primary bounded number of secret keys before challenge cybertext. And after challenge cybertext, it can query any polynomial number of secret keys. I will discuss the notion of arithmetic key gardening scheme. The Garville function takes a function F and the secret beta as input, where F is an ABP from JP to the current JP. Z and X are variables and R belongs to JP to the current M is the randomness. The Garville function outputs level functions L1, L2, Lm plus 1. Suppose these level functions are known for some particular values of X and Z. The level values are L1 to up to Lm plus 1. These level values are now fed into some event algorithm which takes input F and X and outputs the functional value Zfx plus beta. In simulation security, the simulator takes the input F, X and the functional value Zfx plus beta and outputs a set of simulated levels L1, Lm up to Lm plus 1. These level values are identically distributed with the level values output by the Garville algorithm. And we call it simulation security for AKGS. I will discuss some properties of linear function, linear properties of the level functions. Firstly, Li is linear in X that means if we take a product of Li and 1, X it will be the level value of that particular level Li. Li is also linear in X, Z and R and in particular Lm plus 1, Z is equal to Z minus of Rm. Where Rm denotes the Mth component of the vector R. Here algorithm is also linear in the level values L1 to up to Lm plus 1. In order to prove the adaptive security of ABE, LL20 introduced piecewise security motion for AKGS. It has two motions, reverse sampling and marginal randomness. Reverse sample algorithm takes input the level values L2 to up to Lm plus 1, F, X and the functional value Zfx plus beta and simulates the first level L1. Such that the set of level values L1 to up to Lm plus 1 is identically distributed with the level values output by the Garville. This property is called reverse sampling. In the second property, given the level functions for J greater than 1, Lg plus 1 to up to Lm plus 1, we can actually sample the Jth level function Lg uniformly at random. This property is called marginal randomness. LL20 also showed that the partial Garville scheme of IW14 is an AKGS with piecewise security and piecewise security implies simulation security. In inner product function encryption, the key generation algorithm takes input a vector V and outputs a secret key SKV. The encryption algorithm takes input a vector U and outputs a secret key CTU. The decryption algorithm decrypts the cybertext CTU using SKV and outputs the inner product between U and V. In terms of security, given a set of secret key cybertext distribution for beta equal to 0 and beta equal to 1, these two distributions are computationally indistinguishable given inner product of UI0 and VJ0 is equal to inner product of UI1 and VJ1 for every I zone. This is called the function hide and seek of IKV. For our work, we have used IKV in the pairing group model. That means the key generation and encryption algorithm can take the vectors in the power of the source group G2 and G1 respectively. The decryption algorithm uses the pairing operation E and outputs inner product U, V in the power of the target group. We now discuss our one-slot 180 scheme. Suppose we have a function if which consists of an N-prime number of APPs FT where T runs from 1 to N-prime. Now we gargle the function ZT times ZTx plus beta T where ZT and X are variables and beta T are secret. And RT is the randomness used in the gargle algorithm. And beta T are chosen such that summation of beta T is equal to 0. The gargle algorithm outputs the level functions L1T to up to L9 plus 1T. We consider two IPFE scales. The first IPFE used is used to hide the first N level values and the second IPFE is used to hide the N plus 1th level value. First IPFE using the first IPFE will compute so the secret key corresponding to the level functions L in JT for JRs from 1 to N. And using the second IPFE will compute IPFE secret key corresponding to the vector R2,1. While generating ciphertext corresponding to the vector X from a JT we use the first IPFE to compute an IPFE ciphertext for the vector 1,x. Using the second IPFE we compute an IPFE ciphertext for the vector minus 1,jt. Now if you decrypt using the first IPFE then we get to know the first N level values L1T to up to L9T. And if you output the decryption algorithm of the second IPFE then we get to know the N plus 1th level value which is JT minus RTM. Now since we have all the level values in the power of the target group we can apply the evil algorithm. And since evil algorithm of AKGS is linear in the level values therefore we can compute the linear operation in the power of the target group. So each FT will give JT times a TX plus beta T. And if we multiply all these evaluated terms we learn effects transpose of JT. Now recall that our one IPFE scheme is only secured for a single secret key. Since our goal is to prove adaptive simulation security we assume that the adversary is submitting the secret key before challenge ciphertext. The proof of our one-slot one IPFE scheme is inspired by LM20 where we have used pre-MS and Pregnancy technique along with the piecewise secretive AKGS and function-metting secretive IPFE. The one IPFE scheme already supports multi-secret key and single ciphertext since AKGS is insecure for multiple evaluation. For that we first introduce a random element S into the ciphertext vector. Then we move this random element S to the secret key vector using IPFE security. Now using DDH we can argue that the level functions are randomized. However if you look at the decryption and procedure of the function and decryption scheme then the value S is multiplied with the term JT FTX plus beta T. Since this value S is not available to the decryptor the decryption algorithm will not be able to output effects transpose JT. For that we use additional vector A. We are now garbling the function JT times A outer times 50x plus beta T outer such that summation of beta T outer is equal to 0 for each outer. We compute additional IPFE secret key for the vector A comma 0. And for J equal to M plus 1 we compute the IPFE secret key corresponding to the vector RT outer M comma A. While generating ciphertext for the vector X comma Z we generate IPFE ciphertext corresponding to the vector S comma S tensor product X and this ciphertext corresponding to the vector minus S comma S dot JT. Now if you look at the decryption all the level functions are now the linear combination of the level functions LJT iota with the coefficient vector S. Since the event algorithm outputs A dot S dot JT times FTX plus beta T dot S and A dot S is available to the decryptor and the fact that summation of beta T is equal to 0. Therefore the decryptor can easily compute effects transpose JT. Another problem remains is that the encryption algorithm still uses master secret key of the IPFE and our goal is to make the encryption algorithm public. For that we use the notion of slotted IPFE. In slotted IPFE vectors are divided into two slots. One is public slot and encrypted in the public slot requires only master public key and another is private slot and encrypted in the private slot requires master secret key. And function hiding security holds only in the private slot. This is now the original scheme. I will now discuss the security proof of our one slot IPFE scheme. Hybrid 0 is the real experiment where all the algorithms are run honestly. In hybrid 1 we activate the private slot. That means the encryption algorithm will be using master secret key. And the index term we should follow from the slotted correctness of the IPFE.  These inner product values will be now computed through private slots. So, in hybrid 2 we make all the public slots in the cypher text 0 and rearrange the terms so that the inner product between the cypher inspector and the secret key vectors remains unchanged. And hence the security will follow from the function hiding IPFE. Our next rule is to randomize the level functions using phrase the sample random values for r t m and a dot s. So, in hybrid 3 we press the sample those values and the index term we should follow from the m d d h assumption. In hybrid 4 we apply pre-image sample ability technique. The simulator knows the function value mean f corresponding to all the pre-cypher text key queries f. So, it can solve the linear system of equation fx transpose z equal to mean f and get a done effected d such that fx transpose z equal to fx transpose d. We will use this vector d in cypher text vectors. So, we add additional hidden slots minus 1 d t minus 1 z t. And the corresponding vector elements in the secret key vector are all 0. Here we extend the dual system encryption abstraction used by ln 20 into a 3-slotted encryption technique. The first slot is minus 1 z t, the second slot is minus 1 d t and the third slot is minus 1 z t. Our goal is to make all the pre-cypher text secret key queries to interact with only the second slot that is minus 1 d t. For that we consider only the first pre-challenge secret key query and we do it one by one through a loop. In the first hybrid of the loop, we copy the secret key elements from first to third slot. Since first slot and third slot are the same in the cypher text vector, therefore the inner product will remain unchanged. Hence the indistinguish duty will follow from the function ID security of IPFE. Now at this stage we will apply our one key one IPFE scheme security in the third slot and make the element in the third slot from z t to d t. For that we need to introduce some additional hidden subspaces. Now you note that all the other secret keys are interacting with minus 1 z t of the first slot and only the first pre-challenge secret key is interacting with the third slot. Since second slot and third slot are same, therefore we can copy the secret key vector element from third slot to second slot. Now the first pre-challenge secret key is interacting with the second slot which is minus 1 d t and we make the third slot back to the normal stage which is minus 1 z t. We can repeat this technique for all other pre-challenge secret key queries one by one and after this loop all the pre-challenge secret key queries will interact with the second slot. And all post-challenge secret key queries will interact with the first slot and the third slot has worked for us as a temporary o-station. Now we will modify all the post-challenge secret key queries. For the post-challenge secret key queries, since we know the challenge message vectors x z, therefore we can directly put the label values into the ciphertext. Next we will use the simulation security of a kgs to simulate the values using the simulator. But we can see that the simulator still uses a tilde z t f t x plus beta t tilde for simulating the function f t. However the final simulator should be using only fx transpose z for that we use a statistical transformation using beta t tilde. And we use f1 to simulate the value a tilde fx transpose z plus beta 1 tilde and all other functions f t will simulate the value beta t tilde. Finally, hybrid 9 is our simulator where all pre-challenge secret key queries will interact with minus 1 dt and we have used the a kg simulator for all post-challenge secret key queries. So till now what we have seen using a kgs and IPFE we construct one-slot one iffy and we convert the secret key one-slot one iffy scheme into a public key one-slot iffy scheme. How we can convert our one-slot one iffy to one extf iffy scheme. Let us see that. We recall that our one extf scheme has this functionality as follows. The secret key is generated for a function f and a vector y. And the ciphertext is generated for a vector x and a vector z concatenated with another vector w. And the decryption outputs fx transpose z plus y dash plus w. Here we use the linear property of the algorithm. We recall that even algorithm is linear in all the level values. Our idea is to see that if we add any value new to the first level value l1t then the value new will come out of the evaluation and we get jt times fdx plus new plus beta t. Our idea is to use this new to compute the term vector transpose w. For that, for only the first level function we compute ipv secret key for the vector l1t comma y. And during the ciphertext generation process we compute the first ipv ciphertext for the vector 1x comma w. Now you can see that the term y transpose w will be added to each level value l1t. Hence we need to secret share the value y transpose w through all fd. So we introduce additional random element alpha t in the secret key generation process such that summation of alpha t is equal to 1. And new t is added to the value l1t where new t is equal to alpha t times y transpose w. Now if we multiply all the evaluated terms then we can get fx transpose j plus y transpose w which is the required functional value. Using this idea we convert our 1 slot 1 ipv to 1 slot 1 htv. And using the same idea involved in the transmission of 1 slot 1 ipv to 1 slot ipv we convert our 1 slot 1 extv to 1 slot htv. Finally we use AGW20 transmission to convert our 1 slot htv to unbounded slot ipv. Here we note that adversity can only query key number of two ciphertext secret keys. This is due to the fact that we are unable to solve the linear system of equation if the coefficient matrix is available in the exponent of a group. For that we have introduced Q-mini additional hidden subspaces in secret keys and ciphertext to incorporate all the pre-cyphertext functional values into the channel ciphertext. I will now conclude my talk. So in this work we present a functional transmission scheme for attribute weighted sum functionality where the weight functions are arithmetic branching program. The security is defined by adaptive simulation based security model. Our scheme supports unbounded slot with compact ciphertext which means the ciphertext size will not grow with multiple occurrence of a particular attribute in the weight function. Our scheme is secured based on K-lean assumption. So from the technical ground we generalize the Penal-20 framework from attribute based inclusion to functional inclusion or from payload hiding to partially attribute hiding setting. Our one slot scheme the ciphertext size grows with the size of bifit and public part of the message. And additionally for our unbounded slot scheme the ciphertext size grows with the number of pre-channel secret queries. Whereas the semi-adaptively secure FE scheme of AGW-20 the ciphertext size grows with the private part of the message. Therefore it is an interesting open problem to investigate a functional inclusion scheme with adaptive simulation security where the ciphertext size grows with only the size of the private part of the message. Another interesting open problem is to construct a functional inclusion scheme for general circuit or EVPs with selective security and unbounded slot with compact ciphertext based on AWA assumption. Thank you. If you have any question you can discuss during the video.


Hey MTV, we are going to university in our new movie, Life of the Party. So to celebrate, we are here to see if we know our freshers from our pot noodles. As we put each other to the test to see just how much we really know about UK Unileif. Our first question is, what do the letters SU stand for? A, silly underwear. B, student utopia. C, student union. Student union. She. Well, you're right. I wish it was silly and depends. OK, here's the next one. What is a pot noodle? Is it A, the term for when your housemate doesn't wash them dishes properly? B, a cute little plant you and your housemate struggle to keep, or C, the only thing you can afford to eat? C. It's a noodle in a pot. C is correct. C. C it is. C is for cookie. OK, if we invited you to Spoon's, where would we be meeting? A, a posh soup restaurant. B, a cheap and cheerful pub. C, a sports bar. I want there to be a soup restaurant. Yeah, that would be me. So I'm rooting for A. I'm going to say sports bar, but I'm genuinely very confused. Debra. Debra is correct. A cheap and cheerful pub. Spoon's. Way to go, Debbie. Thank you. I know Spoon content. Do you Spoon people? Is that a reference? Is that a reference there? Maybe it's like the game Spoon's. All right, which of these is a traditional Sunday morning ritual for many UK students? A, visiting the parents. B, washing the cars. C, watching the Hollyoaks omnibus. What? I'm going to go with C. C. Because I didn't understand this. Same. And Gillian? C. C is correct. Love it. The Hollyoaks, you don't omnibus. Loose Women is A, a daytime TV show that helps you avoid studying. B, a feminist university society. Or C, the name of a UK sorority. I think B, all of the above. B. B, we're reclaiming it. As a society. Yeah, B. I'm going to go with A. Everyone says B. You're wrong. Uh-oh. It's A, a daytime television show that helps you avoid studying. Of course, Loose Women. Loose Women. Welcome back to Loose Women. In British university culture, what is a fresher? A, a recap or refresher of the work you did this semester before. B, a new student. C, a station where you can shower and clean up if you didn't make it home the night before. Nice. New student. New student, but I wish it was like a dirty station to clean your tail. OK, what is a ring of fire? Is it a drinking game? It's what happens to you after dodgy kebab. The WhatsApp group dedicated to you and your housemate's exes. Ring of fire. That's funny. Ring of fire, guys. Drinking game, dodgy kebab or? Sounds like a drinking game. Yeah. A. It is indeed. Oh. A drinking game. The Ring of Fire. Wonderful. Wonderful. All right. What is the premise of pub golf? A, having a drink at every hole in a golf course. B, it's like football, but with tiny golfers instead of soccer. C, dressing up in golf clothes and having a drink in 18 different pubs. Let it be C. C. B. Yeah, I'm leaning B. She is for the correct answer. Good enough for me. I love that they dress up like they don't play golf. Yeah. No, no, no. They just dress up like they go home. Why would you do it? What is that? Like, khakis in a, in a. Argyle? A visor. Oh. With a, like, with a ball. Yes. Like, I was doing it in 1940s. Like, yuck, yuck, yuck, yuck. Oh, yeah. Liquid is, A, a specific type of cocktail that mixes more types of alcohol than you'd like to count. B, the name of your local nightclub where you regrettably ended up three nights a week. C, C, what you call dish soup as in, mate, can you get some liquid down Tesco Express? C, maybe C, because of that reading. C, because of that convincing reading. A solder with an accent. It's B, the name of your local nightclub where you regrettably ended up three nights a week. Every, Rooney has a nightclub called Liquid? I think you're just like, oh, it's done at Liquid. I was done at Liquid. Things got pretty rough. Yeah, it was probably out by Liquid. Yeah. Staying out at Liquid. Would you post a mic out at Liquid? It's always on loose girls, yeah. Yeah.  Yeah, I saw you at Liquid. Oh, yeah, you like it, don't you? She hit the pressure.


So, we dive into our first panel session for the day and the session will be moderated by Mr. Gaurav Paava, Vice President Sales, we serve, let's welcome our panelist, Mr. Gujjot Shah Singh, Senior Vice President and National Media Head, Densu Webchutney, along with Mr. Nishit Srivastava, CEO, Cuberoot Technologies, along with Ms. Kanika Mittal, Digital Leader. Well, this discussion is going to be about data collection versus data privacy and it's going to tell us as to where we draw the line, where we draw the boundary. I request that we please put our hands together to welcome all our esteemed panelists, ladies and gentlemen. Thank you very much for taking out your precious time to be with us here today and we look forward to listening to you. So, welcome everyone. I think what we are going to discuss today at this panel discussion is very, very pertinent topic. This is about, you know, data collection versus data privacy and where do we draw the line. I think in the morning session, Mr. Badra just gave us glimpses about the digital transformation that we are actually seeing and what we see that as a click of a button, we are buying products, we are consuming a lot of content online, we are expressing our views, opinion with our friends, with the world at large. But what is really happening at the back end, there is a big data machinery, okay, which is working, trying to maneuver us to some desired results by apprehending certain information that we've left or we have shared, you know, intentionally or inadvertently with others. So there is a growing, you know, businesses are evolving and somewhere it is considered very important for businesses because of the, you know, diminishing loyalty that they are seeing from consumers, you know, to constantly innovate and as a result of that, they really are looking at a lot of data points that they can get about their customers. But at the same time, I think there is a proliferation of such businesses who are constantly looking out and searching for more and more insights about its consumers. So I think with keeping this in mind, looking at this aspect, while there is a value in collecting consumer data, how could all this be made less invasive? So I would like to invite, I think, some comments from Gujarat because I think he comes with a background understanding the consumer's perspective and maybe you could open the discussion here, Gujarat. Thank you. Thank you, Gaurav. I think more than just the consumer's perspective, I think we, none of us in the industry would have been successful if you wouldn't have cared about our consumer today. And what I really feel, how to make it less invasive is the only way about that is, I feel, is about telling the customer upfront about where the data is going to be used. Gaurav just mentioned about at times we end up leaving our data behind knowingly, at times unknowingly. I think all of that is happening because we're leaving that one tick mark that we're collecting your data right at the bottom of the screen or somewhere hidden in the screen. I think that's something that we really need to get rid of. Speaking from the consumer's shoes, I think it's very important as a consumer that we should know where our data is getting collected and where is it going to be used. So I think it's very important that we, in this entire, you know, in this entire zone of collecting so much of data, it's important that we move towards consent-based marketing where there is an explicit consent that's been taken from the consumers of where my data will be used. Because if given a choice to me of leaving my data and not leaving my data behind, I need to leave my data behind for me to be convenient about accessing internet today. So that's important for me. So I think consent-based marketing is important as a consumer for me to proceed further in the way I explore things on web. Sure. So Kanika, would you like to add? Yeah, I'd love to and I really like the point that you made about consent marketing.  It's so heartwarming. And to feel the mic in the hand and to feel the player of the lights on the face, it's been like more than two years. So just, I just want to begin by saying a huge thanks to the organizers. It's just great to be here in a hall full of people. Moving back to the topic here that the panel is discussing, I just want to go a step further to what my esteemed panelist just said and add that it depends also on what are the various sources of data that a marketer is using. One, of course, are the channels that is developed and used and maintained by the marketer themselves where consent becomes hugely important. But also at the same time, they're also buying data. They're also interacting with different forms of agencies and partnerships to get the kind of data they need to deliver the right ROI for the business. And I think that's where having a very strong sense of responsibility and a strong sense of balance becomes extremely critical. Many of you are marketers in this room and I'm very sure that you feel the pressure to deliver on ROI, especially when budgets are constrained because your behavior has changed following the pandemic. And in that pressure, there could be a tendency to quickly go after the right kind of data. But I think in that speed of trying to get the data quickly, it's also important to stand back, reflect and very responsibly get the right data and check with your different partners that what are the balances that they have in place? What kind of consent are they taking? Is the consumer aware? How is the data being used? And then kind of take a step forward and use the data responsibly. So I feel like there has to be a strong balance between consent-based marketing that a marketer engages with on their own. But at the same time that the data that they procure, they have to be extra cautious and hold their partners accountable to extremely high standards. Right. Thank you. That was an interesting perspective. So you know, when I really look at what are we really leaving behind as footprints on digital media, our financial information is there, our health records are there. If there is a breach here and there, people panic. And we have seen instances in the past that when the businesses, they are collecting data. They may not be their consumer businesses. However, they're collecting data. They need to really rely on certain partners technology platforms to put it in a perspective to enable them to realize the data properly. And as I said, there could be certain mistakes also that may happen. And the data breaches happen and the panic is there. What needs to be done there when you're talking about mitigating that suspicion or building trust as it is, this is very important. How marketers do that? How you, Nishit, you're a part of a company that manages data of millions of people and help marketers also kind of have deeper insights about their audiences, data-based offerings. Where do you see how do you see this mitigation happening? Thank you, Gaurav. Good afternoon, everybody. As far as your question is concerned, I see regulators and policy makers have a very great role to play. And what we have seen in this last five to six years, the laws and policies in India has still not been populated. The way it has been done in the western countries. So one of the very popular compliance, which has been followed worldwide is GDPR compliance in the European Union. And that is the zenith of the compliance and the policies what our data store, how the data needs to be stored, how it needs to be secured, how it needs to be processed. And there it has been clearly stated that the control should be branded given to the consumer. Most of the times when we are talking to our clients or agencies or marketers, for that matter, we see that that marketers claim that they are the owners of the data for the consumers. Because if you have bought certain product on, let's say, an enormous website, the marketers of the brand assume that they have acquired consumer data also. But as per the policies regulators, it should be explicitly mentioned. And the controls should be given back to the consumer that how that data will be branded by that brand or by that infamous portal. So a lot of things needs to be done here. I see there's a lot of scope here. And one thing is that we are already working with the policy makers, the forums, and they are thinking on it. And you see that all the years, those policies will also be complicated. Ending, you would want the policy. Yeah, that is what I am asking. I'm just talking about bombs here, I think, yeah, cannon bombs, yeah. I just want to ask the policy aspect of it, which is very critical, right? Like the way he said around the creation of the policy and the right implementation of the policy. But also the point of the consumer, at what point does he sort of, you know, reach to certain terms and conditions also matters. Typically, our terms and conditions related to consent of sharing data are sliding in, or sliding on right at the end of the contract, or when you are interested in buying somebody or subscribing to somebody, all of these things come right at the end. And by the time you are pretty much, you know, already at the end of your decision making stage, so you pretty much give what is already for consent, you just give the consent without thinking, or you do it because you are totally not fair to the choice at that sometimes. You want to choose convenience as you know that everything is coming at a price, but you just are left a bit conner and so you go ahead and you give the consent without really wanting to give it. I think the onus of, you know, various industry bodies and all of us also matters in thinking this particular aspect, a little bit more easier for the consumer, when choice to, you know, give the data or not give the data, is actually asked to the consumer at the right time, and not slid in at a point where the consumer will have effective time to make the choice, or they simply go through it in some way. So I think the experience, if I may say, goes hand in hand with policy on really having consumers let us use their data the right way. Does that make sense? Sure, absolutely. And just to add further to that and possibly take your opinion about it, what would you think, I mean, what if there's a regulation and I think somewhere regulator also needs to play a part? You know, the consumer needs to be given enough part, a part to see that what brands are using, what kind of a data about them that the brands are using. So different brands or different categories have, you know, different policy policies. So what you actually, you know, allow a bank to see or your stock broker to see, you may not want a retailer to see. Okay, so somewhere I think that if a regulator also could play a part and, you know, and there's a mechanism which is set up where consumers at large can go across many merchants or, you know, online platform and figure out that what is the kind of a data that those merchants or those platforms have about them and, you know, they have to, they have all the right to revoke the permissions or allow it. So what do you think, Nishit, in terms of the regulator, you know, aspect, where does it come from, what kind of a rule that a regulator could play?  How involved we are here right now and what needs to be done? It's not like that we don't have laws, existing laws on the desk. We have ID Act and, you know, there are certainly 1559 laws which are already informed, you know.  Now, I think it's, as far as the laws and the population is concerned, I think the need of the R and the self-regulation, okay. So we need to, you know, move forward ethically and, you know, in an ethical manner, where we give the control back to the user. There's kind of information, I'm sure that most of the people, you know, sitting in the audience, they don't have any problem with non-personal, undefiled information, that we call it non-PI information, is stored and secured. But the moment it comes to the personally undefiled and identifiable information, it's called PI information coming in place and we, you know, most of the brand of technology company like us, we start storing your personally undefiled information and then this issue starts coming in. So as far as the privacy policy and the usage policy of the website, it should explicitly mention that, you know, what kind of personal, undefiled information that brand or the website or the publisher is using and how it is processing that data.  There was a study done by Sanjeev in 2016 and it may be said that 70% of the people, they were not having an issue, as long as they were, you know, informed, transparently about all the data is in process. You can just use that process, that PI information. Pujo? I love the idea, Gaurav, that she's involved. In fact, you can come after, not just bring it up and build on it. I believe Sanjeev, anyone, Gaurav, can find you to collaborate. I think what you were saying is almost like an aggregator website or an aggregator app. Like you have Trekk, for example, where all your gankas are aggregated and you know exactly, you know, what pieces connect to what is not. Similarly, there's an aggregation somewhere that can be done through a technology company where you must go in, belong to your profile and you see what kind of data is being shared of what kinds of aggregations, whether it's coach media or e-commerce or management or otherwise.  I think that could be brilliant and absolutely destructive. And hopefully, someone in the audience will get inspired and maybe pick that for anything. Like, you know, we have provisions that in our phones, you know, what kind of provisions we try to work all apps. So something similar from a platform perspective. Gurjo, I just wanted to bring this up for you. There's a causal relationship between our actions, our data, and the far-reaching effects, okay? And that's still obscure at this point in time. Should consumers be actually, again, taking a different view about what we are discussing here, but should consumers be really told how the data is being used? Would they not get the chills once they actually get to know what all the information about them is going to be in the world by then or by certain companies? Yeah, so I think I'll first connect a lot backwards in what we've been talking about, giving the control back to the consumer or giving the authority back to the consumer. I don't think there's any giving back. It always stays with the consumer. Whatever data we leave behind as consumers, it's the data of the consumer. Well, I've been a marketer myself for 12 years, but I don't think so any of us would have succeeded if we would have not cared about our consumers like I mentioned earlier, but the control very much stays with the consumer. And I feel that as a consumer, if not tomorrow, see, digital today is not the fourth or the fifth or the sixth preferred medium. As we move along, we've seen humanity and we've seen a mega shift, and we know digital is not just about marketing anymore. It's how our life is being into existence, right? So digital is the most preferred medium. Sooner or later, we all have to accept the transparency. Look at why GDPR laws were created. Europeans, you know, they were very well aware about their laws, which is where they pointed out, hey, why is my data or why are the permissions being taken explicitly? Which is why all over the world, it is now being formed as a GDPR policy. So the faster marketers and brands accept this that you're gonna be telling upfront where my data is going to be used, the better it would be because otherwise it could cause more disruption in the system. And I think users and consumers will only get insecure about it. Honestly, it's a balance that we're going to hit naturally. It's better if we approach it more cautiously and get there faster. So yeah, as a consumer, my data is always mine. The control is never. I think a marketer has enough other powers to live with, so marketer don't need more powers. Let the powers rest where they need to be. And that's how I think we should proceed to a more safer space on internet. Marketers want to make data as their friend and they should know how to manage their friends. That's fair to that, but to Joe's mention, there's a concept called data portability. In the advanced market, when a consumer is told that all their data is still being utilized, all this being processed, so that user and consumer is interested in taking the data back from that technology company or from that provider and put it in a different company. So those kind of laws used to be there where we need, obviously we need to inform the consumer about how the data is being processed. But at the same time, if we empower them by giving them this kind of portability where they can get that right data or whatever information which is being processed back to the user, I think that will create many situations for the entire community. That's very interesting perspective. Generally also, I would be looking forward to kind of figuring out that you also have to work and you have a key and key in place. Typically, what are the checks, internal checks from a stock perspective? You guys have in place to ensure that the privacy is maintained, the data handling, certain policies that you have in your company which gives confidence to consumers, which gives confidence to marketers that they're dealing with the right partner. What are those checks that you want to highlight? Yeah, definitely.  So it's a sensitive subject and the same, you know, if the penalty is huge, you know, we need to sign back in agreement with our data scientists, our technology guys back in the company to ensure that, you know, the data is, you know, secured and they're encrypted in the right manner so that they are not encrypted back and you know, it's not misused. Not coming back, you know, from the market years and from a partner's perspective, a partner's make sure that while they are dealing with consent from their consumer, they mention it explicitly that they are sharing that data with a technology company like us, the third party companies. So that explicit thing is mentioned there and it's part of the GDPR guidelines that we follow and, you know, then consumers opts to process the technology company like us. And they get the data and then we inform them that how we are processing that, what are the data points that we are getting to that and all the data points can be given back to the museum. We opt out features of it at every stage which, you know, every consumer would love to have. Coming back to you, Kanika, just taking your perspective of being an aggressive marketer, to what limits can a marketer really go? Oh my God, there's a tough one, you know. I think just for a little bit of context for our answer to your question, I think times have really changed for marketers. Like there was a time where there was a lot of focus on brand marketing, which is actually meant, you know, the hairless style of marketing where you would use perhaps digital, more television, outdoor, print, et cetera, and really create like a complete, beautiful image of your brand. Then it really took a lot of performance marketing, you know, when Prithora had that first, Prithora of the company came into the country and offered marketers the entire trip through journey where we get the results that they were looking for and most importantly, they would get the attribution that they were looking for. And that temptation, I think, for any marketer was huge. And that was also a time when the industry was really evolving and there were not so many discussions and conversation around data and how to use the data. And there was this whole rush to go in for the bottom funnel or, you know, hit the bottom line using the bottom of the funnel and all of these new tools that were available. And I think that was a time where perhaps many marketers in their regression would abuse these tools very differently, not knowing that tomorrow there's a different aspect unfolding in the future. But now, once, you know, we've all gone through the sea change with the pandemic and the increased awareness has happened with regulation and government talks and several other things. There is definitely increased awareness and sensibility and responsibility with marketers today and two things are emerging out of that. One, there is a better balance coming within the realm of brand performance marketing. And strategy-making data is why both performance and brand marketing. And today there's a sense of balance. Companies want to do very meaningful, very purposeful communication. They want to tell the right stories. They want to have an effective presence of social media where they're able to build their personality, have a tone and connect with their consumers. And that they can do independent of deep data. And then there's another side to it, which is the performance marketing in which they are now balancing with brand marketing and say, what do we need? Where do we need? Where do we need? And what's the best way to get it? And so it's a lot more sensitized. It's a lot more careful. And I think, and that sense of balance and responsibility is really making this move to take very well. So I think why we tread on this kind of helping this conversation, the colors, which creates this, there's a better balance between brand and performance. And the second is that, you know, just to know the sheer industry level awareness, all of us in this room today having this conversation is a clear testament to the fact that anyone listening to us or going back, simply in their subconscious mind will be more assessor and more careful about what it was said that would be in the future. So the sheer, with horror of conversation with the market and the industry with peers is building a collective sense of responsibility. And I think even though marketing is said to get very aggressive, this sense of responsibility is now here to say, who to make. Right, thank you. I think, good job, one perspective that I really wanted to have from you. You have consulted, probably more than 200 brands in your career, you know, and you've been a part of a lot of what's been in campaigns as well. How tempted are you to, again, you know, from a marketing perspective there, you know, from an advertising perspective, or an agency perspective, how tempted are you to leverage an understanding of campaign of one brand for another brand, okay? Because there is a data there, okay, which talks about, this is a market that perform well for this particular brand. And we're talking about one regular, 21 regular, you know, you figure out that, you know, down south in Kerala, this brand performs well. Okay, so that's a data, that's a take away data point for an agency. Typically that belongs to a marketer, you know, from that perspective.  How far could you take that, or you know, what is the kind of of agreements that you have with your brands to protect that sort of, you know, kind of the data or privacy from that sense? Okay, so Gaurav successfully pushed me back to a marketeer's shoe from a consumer's shoe. They called you always, wear two hats, I wear two turbos for customer in a marketeer. So now talking from a marketeer's lens firstly, more than just brands at Denso, we are, we're bloody serious about data privacy and regulations. So once, so I think we are one of the few agencies and group who have a data protection officer in India, not just outside India as well. There are very few and I think only, I think there would be two at an overall level in India. We've been having a data protection officer for almost over two years now. So coming back to the point that you mentioned as a marketeer, I think as marketeers, when we take out inferences and learnings from some data that exists for one brand or for one market, et cetera, the inferred learning that we extract from any data and that learning is applied anywhere else, I think that's not a breach of data because that's a learning interpreted by a marketeer individually. However, on the other hand, no data can ever be cross-pollinated within Denso. We swore on to that. And I think that should be any marketeer's rule of operation that there should be no data migration, but of course, there has to be learnings that migrate from one brand, one category to the other. That's what a marketeer does in the course of executing successful marketing campaigns. Yeah, I think so we are pretty much covered a whole lot of issues around the subject. And I made some notes and if I were to kind of sum it up, I really feel that data privacy is tied to customer experience. I think in addition to providing best products and services, businesses must also provide consumers a sense of security as it pertains to their personal life. Enterprise needs to really stay up front to consumers and that's what consumers would appreciate that what kind of data about them, where the companies are using, what value that you could add to a consumer to their business or to third party. I think that upfront stating that should work well to build that trust. And then we also talked about putting the power in the hands of customers, yeah. Importance of consent needs to be realized by the company's consent management systems needed to be put in place. And consumers to be made aware that every business has a privacy policy. Right? So finally enterprises are also ambitious, right? And they want to push boundaries. They really want to push. If you keep playing safe, safe all the time you may not be able to innovate, okay? In order to innovate you will have to push boundaries. However, they have to really carefully play a maker checker there themselves. And the regulator also need to come and play their part, make consumers aware of their rights, of the privacy policies. And once the regulator somehow comes and takes a point, takes a position, I think market is good also for you, right? To build that trust. So I think just overall to summit, if you really say that between, you know, kind of figure out that between data collection and data privacy, where to draw a line, we may not have a black and white. You know, answer to that. We can't put it in black and white. But definitely as we tried putting it all together there are regulators, there are corporates, there are consumers who together can, you know, come together to evolve this entire ecosystem and make this a built-in situation for everyone. I think with that we would like to end and open the floor for any queries that you may have. We would be happy to address it. Please introduce yourself and let us know for whom the query is meant for. Sure. All right. I'm Karan, I grant digital for darkness cement. So news broke yesterday that Facebook is going to take away race and religion as data points in the US. As marketeers who primarily work in the Indian markets and knowing the data sets we have available, what data sets do you think should ideally be taken away so that it makes the consumers' life on digital safer while leaving all the commercial value that we as marketeers have in place? So any thoughts on that based on the data sets that we do have available now? Revolvitators, Alokan, yeah. It was a very interesting question. I thought we answered the reverse. I think the data sets that are needed are perhaps, you know, more demographic and sociographic and pro-national in nature because they help to build the customer's profile, you know, like his life, his interests so that the brand can serve him in the best way. So what I would say is that look at it the other way. What are the data points really needed to build the right type of customer profile that makes a marketeer or rather gives the marketeer better insight into how to serve him? And whatever data sets don't see into that profile or are just additional information, just remove those. So I think that's the best way I can answer this. Adding a little more to that, I think Facebook and Google are very popular platforms. But like how Gaurav started right in the beginning about digital transformation, you don't know how many other technology players or media partners are capturing all that information. Today I also leave information about my salary in my messages and I allow Google to read my messages and there you go. All the micro-investment apps are reading my salaries. They're reading where am I investing? They're reading, Facebook is reading. I'm eating Maggie because I'm posting about having Maggie with my nephew. I'm posting about move to a new city. I'm posting about all my habits. I think what's important is in some way knowingly or unknowingly there are many data sets that are being created but it's very important that when I'm leaving any of this information behind I should be told explicitly as a consumer it's my right to know explicitly that where all this data is going to be used. Is eating Maggie with my nephew gotta be used later to retarget me or not? Probably that's something, like I said we're gonna naturally find a balance between the black and white. Gaurav I think the black and white doesn't exist now but hopefully maybe next six months, one year when we hit the stage again there will be a black and white. So we should just be explicitly told and there are many data sets that exists. Sure and again the power to the consumer at the end of the day if he knows what about him is known to anybody, any third party he should have that transparency with him and the power to revoke those permissions if at all. Thank you very much Mr. Gaurav and thank you very much. Thank you very much Mr. Gaurav. Thank you Mr. Nishit and yes Ms. Kanika Mital thank you very much. That was very, very good and thank you for taking us through some fantastic highlights that we all got to know about and on that note I'd like to request Mr. Sanjay Sundewani CEO Indian Express online to please come up on stage and give a token of appreciation to our esteemed panelists and can we please put our hands together? Thank you so much.


It's time for the Lawn Jean Chronoscope, a television journal of the important issues of the hour brought to you every Monday, Wednesday, and Friday, a presentation of the Lawn Jean Wittner Watch Company, maker of Lawn Jean, the world's most honored watch, and Wittner, distinguished companion to the world-honored Lawn Jean. Good evening. This is Frank Knight. May I introduce our co-editors for this edition of the Lawn Jean Chronoscope? Larry LeSœur and August Hex, your chief editorial writer for the New York Herald Tribune. Our distinguished guest for this evening is the Honorable Maurice Coug de Merville, French Ambassador to the United States. Well, this may be the first appearance of the new French Ambassador on American television. Coug de Merville is no stranger to this country. He's made friends and influenced people from Washington to the Council Chambers of the North Atlantic Featy Organization. Mr. Ambassador, we're happy to roll out the Red Carpenter friendship to you, but I must confess that the people of this country are a bit critical of France for some reasons. I wonder if you have any answers to those criticisms. Well, I suppose you are referring mainly to the political instability of France, which the friends of France abroad are worried about, and which, of course, the Frenchmen are even more worried about. I think that this political instability is due to two main reasons. One is the constitution of France, which is drawn in such a way that the executive is too weak, and maybe the legislative is too powerful. Another reason, I think, is that the proportional representation, which is our electoral system, gives always a sort of splitting of the political parties, the consequence of which is that the political parties are too numerous. This is, of course, a weakness, but I must underline that behind this political instability there is all the same in my country, a very permanent stability, which is manifested mainly by the stability of the administration, the civil service, as you call it, I think, which doesn't change with the government, which is permanent. It is true that the predecessor, Monsieur Bonnet, was here for 10 years, wasn't he? Yes. In this country. Well, I think this is a very good example of what I was calling the stability of the administration in France. Does that mean that Mr. Ambassador, that you expect to be here for 10 years, too? Well, I couldn't predict what will be going on with me. My answer would be that I would, of course, be very pleased if this happened. Well, Mr. Ambassador, turning from the political to the economic field, there are certain worries that Americans always have about the French economic situation. What would you say of that? Well, I would say on that that you don't need worry now. The economic situation of France, as well, I think, as the economic situation of all the countries of the free world, is steadily improving. In France, now the period of reconstruction is completely over. And the production is, again, developing very much. For instance, I could say that the industrial production of France is now a little more, I think, than 50 percent over the industrial production of the pre-war period. And on the other hand, the inflation, which had been a menace in the seven or eight years after the war, is now completely checked. And I think I don't exaggerate in saying that the stability of the, in the monetary field is now completely re-established, which is, I think, a good sign of economic health. Mr. Ambassador, the important committees of the French Senate have given rather solid majorities to the Paris agreements on German rearmament. What conclusions should we draw from those passages and majorities? Well, I think it's a very good omen for the final ratification of the Paris agreements by the Council of the Republic, which is, as you know, the last step in the process of ratification of those Paris agreements by our parliament. I think that the majority in the Foreign Relations Committee in the Council of the Republic was a big one. And I hope that it's a sign that those agreements will now be ratified by the Council itself in the near future. The French Prime Minister, Monsieur Four, has said, I think that once these accords are ratified, that the next stage for France will be building the hydrogen bomb. Does that seem to you like a good idea? Well, I should say that's quite another proposition. But of course it's a very important problem. And I think that my country, as well as all the big powers with an army and a big military effort to maintain, my country has to be worried with that problem. Because more and more the atomic weapon is becoming a normal weapon in the modern army. And I don't believe that such an army could be maintained at a high level of efficiency in the future without having atomic weapons. Whether that will be done soon in France, I can't know. And then of course it's a tremendous job to be made. But what I can answer to your question is that it is certainly a problem and we will have to deal with it. Monsieur Ambassador, France of course is a world power, so I'd like to run around the world, if I may, figuratively of course. Now we've heard rumors of friction between the French and the American military in free Vietnam, South Vietnam. What is at the bottom of those rumors? Well, I don't think there is anything, there is anything real in those rumors. I've heard of them also, but I've heard also very often repeated that the cooperation between the two high ranking officials, which are in Indochina now, for the American side and for the French side, I mean General Collins and General Haley, that cooperation is very good. And I think it's really the basis of the situation now. There may be difficulties there between friendly and free countries. There are always discussions, points of view are not always the same, it's quite natural, but when there is a friendly spirit, those difficulties can always be solved. Do you think as a result of that cooperation that South Vietnam, free Vietnam will remain an independent country and not become communist? Well, it's of course difficult to predict the future. I think that what's important in South Vietnam now is two things. One, that the close cooperation which exists for the time being between the Americans and the French goes on. And the second is that the Vietnamese government should be steadily strengthened. If those two conditions are fulfilled, I think there is some hope that the South Vietnam can be defended against the communist menace. Mr. Ambassador, France's chief sphere of influence seems to me to be in North Africa. Now the previous Premier of France, Mandus France, did enact laws which gave more power to the Arab natives of North Africa. Do you think that the present government of Mr. Ford will continue along those lines? I don't think that on the basic principles of our policy in North Africa, the new government that has taken the place of the Mendes France government will do anything different. I think the principles will be the same, which is granting progressively more and more political autonomy to the states of North Africa. Maybe in some problems the matters could be different. Maybe for some specific question the practical solution would not be the same, but that doesn't matter really. I think in general that the policy won't be changed. Well, Mr. Ambassador, you say if the policies aren't changed, what actually is the philosophy of the new Premier of France, Mr. Edgar Ford? Are they widely different from Mendes France in any way? Well, I should say, to that I should say that it's more a problem of personality than a problem of policy. I think Mr. Edgar Ford is more the middle of the roads, the type of man. Mr. Mendes France was a very strong personality with very definite views on all the problems. Mr. Edgar Ford probably has, of course, very definite views on the problems, but his way of getting to the solutions may be a bit different from those of his predecessor.  I'm quite sure he is, as many Frenchmen, anxious to change some parts of the constitution. You saw that in our parliament those last days a proposal was made by a former prime minister of France to change drastically some parts of the constitution and this has already had a great following. Mr. Mendes, of course, you've had much experience throughout the world. You've been in Russia, you've been in Egypt, you've been at the councils of the NATO powers. Do you feel that the world is moving towards war or is it possibly moving towards peace? That's a very difficult question to answer, of course, and I don't want to answer it with too much wishful thinking, but I should say in the main that my impression is rather optimistic. I think the prospects of peace are better now than they were, let's say, three or four years ago. For instance, when the Korean War began. Well, thank you very much, Mr. Ambassador. It's been a great pleasure to have you here tonight. The opinions expressed on the Launcine Chronoscope were those of the speakers. The editorial board for this edition of the Launcine Chronoscope was Larry Lecer and August Hector, our distinguished guest was the Honorable Maurice Coup de Merville, French Ambassador to the United States. Launcine is indeed helping to make important sports news. In this month of March, there are 22 major sports events on the Launcine calendar. For the official timing of these, some $100,000 worth of Launcine Olympic timers, the world's finest timing watches will be employed. Among these front page events are the United States Nationals and the United States Olympic Ski Trials at Franconia in New Hampshire. The American International Ski Meet at Stowe, Vermont. The Knights of Columbus track meets in New York and in Cleveland. The Chicago Daily News meets at Chicago. The Eastern International Swimming Championship at New Haven, Connecticut. The NCAA and the AU basketball championships in Kansas City and in Denver. And the Mobile Gas Economy Run Los Angeles to Colorado Springs in Colorado. The Launcine watches used for timing these sporting events are blood brothers to the Launcine watches which are so conclusively the first choice of discriminating men and women on five continents. Launcine watches are as outstanding for elegance as for greater accuracy. Launcine watches are made to an ideal of perfection which has guided its makers for close to a sensory. Throughout the world no other name on a watch means so much as Launcine. The world's most honored watch, the world's most honored gift, premier product of the Launcine Wittner Watch Company since 1866. Maker of watches of the highest character. We invite you to join us every Monday, Wednesday and Friday evening at this same time for the Launcine Chronoscope, the television journal of the important issues of the hour. Broadcast on behalf of Launcine, the world's most honored watch and Wittner Distinguished Companion to the World Honored Launcine. This is Frank Knight reminding you that Launcine and Wittner watches are sold and serviced from coast to coast by more than 4,000 leading jewelers who proudly display this emblem. Agency for Launcine Wittner Watch.


as an asset. So I'm going to say existing contact let's put let's just copy the name where's the name office depot I can copy it from here copy that boom office depot and I'll say under a thousand well no let's just call it office depot what are you doing that's okay there's our our new vendor and then we're going to stay down here that this needs to go to supplies supplies and then I'm not doing the location thing well that was our new location field we played with last time we won't but you could assign it to a location because we added that here and then reference I'm going to say it applies to all the accounts and the name of the rule office depot under one thousand dollars all right so there it is let's go ahead and save it and then now this might be the only rule that you apply right because I can go into here and say okay this one's good under a thousand no problem and this one is good it's under a thousand let's pull that one in this one office depot didn't apply the rule because it's over a thousand dollars right so so it applied so it didn't apply that rule there that's what we want now you could leave it like that you could just say well if it's over a thousand dollars then I'm going to decide whether or not I want to put it on the books as supplies or as equipment of some other equipment account because I might then have to decide if I need to put it into equipment or tools or you know whatever a category but usually it would be equipment or what we will do shortly is make another rule that will say if it's over a thousand dollars you want to put it into the fixed asset all right so I'm going to go to the tap let's go and see what we've done so far before we do that update the balance sheet so checking accounts going down so that's no I don't even need to look at it because we've done that we see we that's that's uh whatever and go to the income statement and in supplies we recorded the supplies according to the rule straightforward except that we had that dollar limit restricting the other stuff so there's these pulling in movie b to the end spend money form bn so it looks good let's go to the first tab again and now let's create the other rule saying hey look if it's from office depot and over a thousand put it into equipment not supplies so we're going to hit the drop down but not too hard just tap the drop down create a bank rule and let's make another one and we want all conditions so all the conditions must be met one any text the normal part of the rule if it contains office depot that's one bit but we have another whole piece whole component down here you also have to this has to happen as well or else you can't do it don't do the rule zero so it has to be a greater than a thousand dollars so there we have it so now we have one rule under a thousand one greater than a thousand now you might be saying well what if I had a bill for exactly a thousand dollars well then the you know the two rules might not catch it and you'd have to put it but you could make a third rule that said it was equal to a thousand dollars if you really want to but you probably be pretty safe with just the two rules you can make it even more precise you could put pennies on it so that you know it would be down to the penny instead of to the dollar and you'd only have if it was you know or whatever so but we'll keep it like that I think we'll be okay so then I'm going to also say this is office depot same vendor and then this is going to be equipment and okay and then I'm going to say reference all accounts and then office depot over one thousand dollars let's go ahead and save it and check that out so now it's applying this rule here so it applied it there now it's picking that up boom shaka laka here's this under rule here's the over rule and uh and here's the under rule all right let's go to the balance sheet and see what happens k posso k in the world posso over here k for the love of deals posso all right so then we're going to say that uh the checking account went down and the equipment account went up so if I go into the equipment account uh we can see then we had the change happening it's happening here so uh office depot there for the over if it's over a thousand and then and then on the other side if all the stuff that was under went to of course once again the supplies account was updated supplies all right and so if I go to the first tab we can check out those rules if we want to modify the rules by the way I can go to the accounting drop down a bank accounts and we can check out all these rules that we've been making all these super cool rules you know I used to not like rules but when I'm making the rules then they're excellent I make good rules other people don't make good rules that's the problem people make the rules that I have to follow they don't know what they're doing but when I'm making the rules then then the rules are perfect so if it's office depot under a thousand office depot over if you if you needed to edit this thing then you go into it and you can make your modifications over here so there we have that so that looks good now just a quick note that if I go to the balance sheet uh we have the items in the equipment you might be asking well when are we going to expense these items we're going to expense them in the form of depreciation and that will typically happen in the united states you might want to track that again with a separate schedule with the tax depreciation schedules because you're going to have to add it to the tax depreciation anyways and and then you can get the depreciation schedules from there either on a tax basis if you want to run your books on the tax basis to match the tax code or you can have it do it on a on a on a book basis uh possibly most a lot of software can do that and then we would do periodic adjustments possibly at the end of the month possibly at the end of the year which usually have another account which would be uh credit to to you know accumulated depreciation for the equipment and once we start adding those separate accounts for equipment automobile and stuff zero has this really nice editing layout item down here that allows us to group for example the equipment account to the related accumulated depreciation we can put the equipment on top even though the the the alphabetical order would be reversed so really nice flexibility to customize our statement more so i think than other software like quickbooks online with sorting out the equipment so that's how that would generally work


I've mentioned before how I have a dislike for writers that emphasize style over story, but of course with with every rule and every preference like that there are going to be exceptions and this is one of them. This collection of stories by Joanna Russ is some of the best writing I've ever read, some of the best science fiction and weird fiction I've ever read. There are a lot of stories in here, most of them are very short, look how many and there's a wide variety of both subject matter and styles in here. She experiments with all sorts of different approaches to storytelling in here. Some of them are so bizarre that they're incoherent and that's the kind of thing that I don't like. It's specifically the sort of thing that I don't like from writers like Roger Zalazny and basically any cyberpunk style writer, but most of the stuff in here is so beautiful that I have to give it my highest recommendation, particularly if you're looking for women writers in science fiction and women's issues in science fiction I would recommend this. For example how Dorothy kept away the spring is one of the most beautiful things I've ever read. It's almost poetry really, it's very short and it's it's so closely tied to the experience of women that I must be missing half of the meaning of the story and half of the feeling of the story simply because I'm not a woman and then there's some nonfiction in here as well. For example she writes about cliches in science fiction that she's sick of, first of which is the weird ways of getting pregnant story. This is the 1970s when she was writing this.  It's one of the most interesting science fiction stories I've ever read. It's difficult for me to describe it without giving it away. Again it's so short. If you want to pause the picture and look at the first couple of paragraphs there you're welcome to it. So Joanna Russ, highly recommended.