129 citations · 740 across the 61 of their papers we have counts for
5 papers · 2 filters
DefensiveDR: Defending against Adversarial Patches using Dimensionality Reduction
Nandish Chattopadhyay, Amira Guesmi, Muhammad Abdullah Hanif +2
Adversarial patch-based attacks have shown to be a major deterrent towards the reliable use of machine learning models. These attacks involve the strategic modification of localize…
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches
Nandish Chattopadhyay, Amira Guesmi, Muhammad Abdullah Hanif +2
Adversarial attacks present a significant challenge to the dependable deployment of machine learning models, with patch-based attacks being particularly potent. These attacks intro…
Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook
Amira Guesmi, Muhammad Abdullah Hanif, Bassem Ouni +1
In this paper, we present a comprehensive survey of the current trends focusing specifically on physical adversarial attacks. We aim to provide a thorough understanding of the conc…
DAP: A Dynamic Adversarial Patch for Evading Person Detectors
Amira Guesmi, Ruitian Ding, Muhammad Abdullah Hanif +2
Patch-based adversarial attacks were proven to compromise the robustness and reliability of computer vision systems. However, their conspicuous and easily detectable nature challen…
PoisonedGNN: Backdoor Attack on Graph Neural Networks-based Hardware Security Systems
Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif +2
Graph neural networks (GNNs) have shown great success in detecting intellectual property (IP) piracy and hardware Trojans (HTs). However, the machine learning community has demonst…