1.5k citations · 3.1k across the 169 of their papers we have counts for
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Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Model
Alon Zolfi, Shai Avidan, Yuval Elovici +1
Deep learning-based facial recognition (FR) models have demonstrated state-of-the-art performance in the past few years, even when wearing protective medical face masks became comm…
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples
Yi Xiang Marcus Tan, Penny Chong, Jiamei Sun +3
Few-shot classifiers have been shown to exhibit promising results in use cases where user-provided labels are scarce. These models are able to learn to predict novel classes simply…
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…
Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems
Ron Bitton, Nadav Maman, Inderjeet Singh +3
Although cyberattacks on machine learning (ML) production systems can be harmful, today, security practitioners are ill equipped, lacking methodologies and tactical tools that woul…
The Threat of Offensive AI to Organizations
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak +7
AI has provided us with the ability to automate tasks, extract information from vast amounts of data, and synthesize media that is nearly indistinguishable from the real thing. How…
CAN-LOC: Spoofing Detection and Physical Intrusion Localization on an In-Vehicle CAN Bus Based on Deep Features of Voltage Signals
Efrat Levy, Asaf Shabtai, Bogdan Groza +2
The Controller Area Network (CAN) is used for communication between in-vehicle devices. The CAN bus has been shown to be vulnerable to remote attacks. To harden vehicles against su…