Analysis of Adversarial Image Manipulations
Ahsi Lo Gabriella Pangelinan Michael C. King
As virtual and physical identity grow increasingly intertwined, the
importance of privacy and security in the online sphere becomes paramount. In
recent years, multiple news stories have emerged of private companies scraping
web content and doing research with or selling the data. Images uploaded online
can be scraped without users' consent or knowledge. Users of social media
platforms whose images are scraped may be at risk of being identified in other
uploaded images or in real-world identification situations. This paper
investigates how simple, accessible image manipulation techniques affect the
accuracy of facial recognition software in identifying an individual's various
face images based on one unique image.