51 citations · 132 across the 17 of their papers we have counts for
17 papers
PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against Emergency Vehicle Lighting
Elad Feldman, Jacob Shams, Dudi Biton +7
The safety of autonomous cars has come under scrutiny in recent years, especially after 16 documented incidents involving Teslas (with autopilot engaged) crashing into parked emerg…
A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories
Jacob Shams, Ben Nassi, Satoru Koda +2
In this paper, we propose a privacy-enhancing technique leveraging an inherent property of automatic pedestrian detection algorithms, namely, that the training of deep neural netwo…
SoK: On the Offensive Potential of AI
Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human +13
Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revea…
Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World
Dudi Biton, Jacob Shams, Satoru Koda +3
The traditional learning process of patch-based adversarial attacks, conducted in the digital domain and then applied in the physical domain (e.g., via printed stickers), may suffe…
The Adversarial Implications of Variable-Time Inference
Dudi Biton, Aditi Misra, Efrat Levy +6
Machine learning (ML) models are known to be vulnerable to a number of attacks that target the integrity of their predictions or the privacy of their training data. To carry out th…
Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs
Eugene Bagdasaryan, Tsung-Yin Hsieh, Ben Nassi +1
We demonstrate how images and sounds can be used for indirect prompt and instruction injection in multi-modal LLMs. An attacker generates an adversarial perturbation corresponding…