197 citations · 299 across the 47 of their papers we have counts for
9 papers · 1 filter
Human-Producible Adversarial Examples
David Khachaturov, Yue Gao, Ilia Shumailov +3
Visual adversarial examples have so far been restricted to pixel-level image manipulations in the digital world, or have required sophisticated equipment such as 2D or 3D printers…
Limitations of Face Image Generation
Harrison Rosenberg, Shimaa Ahmed, Guruprasad V Ramesh +2
Text-to-image diffusion models have achieved widespread popularity due to their unprecedented image generation capability. In particular, their ability to synthesize and modify hum…
Exposing and Addressing Security Vulnerabilities in Browser Text Input Fields
Asmit Nayak, Rishabh Khandelwal, Kassem Fawaz
In this work, we perform a comprehensive analysis of the security of text input fields in web browsers. We find that browsers' coarse-grained permission model violates two security…
SEA: Shareable and Explainable Attribution for Query-based Black-box Attacks
Yue Gao, Ilia Shumailov, Kassem Fawaz
Machine Learning (ML) systems are vulnerable to adversarial examples, particularly those from query-based black-box attacks. Despite various efforts to detect and prevent such atta…
Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks
Ashish Hooda, Neal Mangaokar, Ryan Feng +3
Adversarial examples threaten the integrity of machine learning systems with alarming success rates even under constrained black-box conditions. Stateful defenses have emerged as a…
Unpacking Privacy Labels: A Measurement and Developer Perspective on Google's Data Safety Section
Rishabh Khandelwal, Asmit Nayak, Paul Chung +1
Google has mandated developers to use Data Safety Sections (DSS) to increase transparency in data collection and sharing practices. In this paper, we present a comprehensive analys…
The Overview of Privacy Labels and their Compatibility with Privacy Policies
Rishabh Khandelwal, Asmit Nayak, Paul Chung +1
Privacy nutrition labels provide a way to understand an app's key data practices without reading the long and hard-to-read privacy policies. Recently, the app distribution platform…
How Interactions Influence Users' Security Perception of Virtual Reality Authentication?
Jingjie Li, Sunpreet Singh Arora, Kassem Fawaz +6
Users readily embrace the rapid advancements in virtual reality (VR) technology within various everyday contexts, such as gaming, social interactions, shopping, and commerce. In or…
Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks
Ryan Feng, Ashish Hooda, Neal Mangaokar +3
Recent work has proposed stateful defense models (SDMs) as a compelling strategy to defend against a black-box attacker who only has query access to the model, as is common for onl…