A Novel IoT Trust Model Leveraging Fully Distributed Behavioral
  Fingerprinting and Secure Delegation
Marco Arazzi Serena Nicolazzo Antonino Nocera
With the number of connected smart devices expected to constantly grow in the
next years, Internet of Things (IoT) solutions are experimenting a booming
demand to make data collection and processing easier. The ability of IoT
appliances to provide pervasive and better support to everyday tasks, in most
cases transparently to humans, is also achieved through the high degree of
autonomy of such devices. However, the higher the number of new capabilities
and services provided in an autonomous way, the wider the attack surface that
exposes users to data hacking and lost. In this scenario, many critical
challenges arise also because IoT devices have heterogeneous computational
capabilities (i.e., in the same network there might be simple sensors/actuators
as well as more complex and smart nodes). In this paper, we try to provide a
contribution in this setting, tackling the non-trivial issues of equipping
smart things with a strategy to evaluate, also through their neighbors, the
trustworthiness of an object in the network before interacting with it. To do
so, we design a novel and fully distributed trust model exploiting devices'
behavioral fingerprints, a distributed consensus mechanism and the Blockchain
technology. Beyond the detailed description of our framework, we also
illustrate the security model associated with it and the tests carried out to
evaluate its correctness and performance.