Analysis of Adversarial Image Manipulations
This addresses privacy risks for social media users whose images are scraped without consent, but it is incremental as it builds on existing research on adversarial manipulations.
The paper investigates how simple image manipulations affect facial recognition accuracy, finding that certain techniques can reduce identification rates, though specific numbers are not provided.
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.