198 citations · 538 across the 86 of their papers we have counts for
6 papers · 1 filter
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…
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…
Seeds Don't Lie: An Adaptive Watermarking Framework for Computer Vision Models
Jacob Shams, Ben Nassi, Ikuya Morikawa +3
In recent years, various watermarking methods were suggested to detect computer vision models obtained illegitimately from their owners, however they fail to demonstrate satisfacto…
Dodging Attack Using Carefully Crafted Natural Makeup
Nitzan Guetta, Asaf Shabtai, Inderjeet Singh +2
Deep learning face recognition models are used by state-of-the-art surveillance systems to identify individuals passing through public areas (e.g., airports). Previous studies have…
The Translucent Patch: A Physical and Universal Attack on Object Detectors
Alon Zolfi, Moshe Kravchik, Yuval Elovici +1
Physical adversarial attacks against object detectors have seen increasing success in recent years. However, these attacks require direct access to the object of interest in order…