29 citations · 40 across the 8 of their papers we have counts for
8 papers · 1 filter
AdvScan: Black-Box Adversarial Example Detection at Runtime through Power Analysis
Robi Paul, Michael Zuzak
TinyML models deployed on edge devices are increasingly adopted in safety/security-critical applications, making them a prime target for adversarial example (AE) attacks where inpu…
Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees
Katsuaki Nakano, Reza Fayyazi, Shanchieh Jay Yang +1
Recent advances in Large Language Models (LLMs) have driven interest in automating cybersecurity penetration testing workflows, offering the promise of faster and more consistent v…
LLM Embedding-based Attribution (LEA): Quantifying Source Contributions to Generative Model's Response for Vulnerability Analysis
Reza Fayyazi, Michael Zuzak, Shanchieh Jay Yang
Large Language Models (LLMs) are increasingly used for cybersecurity threat analysis, but their deployment in security-sensitive environments raises trust and safety concerns. With…
Michscan: Black-Box Neural Network Integrity Checking at Runtime Through Power Analysis
Robi Paul, Michael Zuzak
As neural networks are increasingly used for critical decision-making tasks, the threat of integrity attacks, where an adversary maliciously alters a model, has become a significan…
ProveRAG: Provenance-Driven Vulnerability Analysis with Automated Retrieval-Augmented LLMs
Reza Fayyazi, Stella Hoyos Trueba, Michael Zuzak +1
In cybersecurity, security analysts constantly face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 vulnerabilities identified since 19…
Exploiting Logic Locking for a Neural Trojan Attack on Machine Learning Accelerators
Hongye Xu, Dongfang Liu, Cory Merkel +1
Logic locking has been proposed to safeguard intellectual property (IP) during chip fabrication. Logic locking techniques protect hardware IP by making a subset of combinational mo…