5 citations · 7 across the 4 of their papers we have counts for
5 papers
FRAME : Comprehensive Risk Assessment Framework for Adversarial Machine Learning Threats
Avishag Shapira, Simon Shigol, Asaf Shabtai
The widespread adoption of machine learning (ML) systems increased attention to their security and emergence of adversarial machine learning (AML) techniques that exploit fundament…
Mind the Web: The Security of Web Use Agents
Avishag Shapira, Parth Atulbhai Gandhi, Edan Habler +1
Web-use agents are rapidly being deployed to automate complex web tasks with extensive browser capabilities. However, these capabilities create a critical and previously unexplored…
CodeCloak: A Method for Evaluating and Mitigating Code Leakage by LLM Code Assistants
Amit Finkman Noah, Avishag Shapira, Eden Bar Kochva +4
LLM-based code assistants are becoming increasingly popular among developers. These tools help developers improve their coding efficiency and reduce errors by providing real-time s…
Attacking Object Detector Using A Universal Targeted Label-Switch Patch
Avishag Shapira, Ron Bitton, Dan Avraham +3
Adversarial attacks against deep learning-based object detectors (ODs) have been studied extensively in the past few years. These attacks cause the model to make incorrect predicti…
Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors
Avishag Shapira, Alon Zolfi, Luca Demetrio +2
Adversarial attacks against deep learning-based object detectors have been studied extensively in the past few years. Most of the attacks proposed have targeted the model's integri…