5 papers
CacheTrap: Unveiling a Stealthier Gray-Box Trojan against LLMs
Mohaiminul Al Nahian, Abeer Matar A. Almalky, Gamana Aragonda +6
The rapid advancement of large language models (LLMs) has sparked growing interest in understanding their security vulnerabilities, particularly Trojan attacks that enable stealthy…
EIM-TRNG: Obfuscating Deep Neural Network Weights with Encoding-in-Memory True Random Number Generator via RowHammer
Ranyang Zhou, Abeer Matar A. Almalky, Gamana Aragonda +4
True Random Number Generators (TRNGs) play a fundamental role in hardware security, cryptographic systems, and data protection. In the context of Deep NeuralNetworks (DNNs), safegu…
Compromising the Intelligence of Modern DNNs: On the Effectiveness of Targeted RowPress
Ranyang Zhou, Jacqueline T. Liu, Sabbir Ahmed +2
Recent advancements in side-channel attacks have revealed the vulnerability of modern Deep Neural Networks (DNNs) to malicious adversarial weight attacks. The well-studied RowHamme…
DNN-Defender: A Victim-Focused In-DRAM Defense Mechanism for Taming Adversarial Weight Attack on DNNs
Ranyang Zhou, Sabbir Ahmed, Adnan Siraj Rakin +1
With deep learning deployed in many security-sensitive areas, machine learning security is becoming progressively important. Recent studies demonstrate attackers can exploit system…
DRAM-Profiler: An Experimental DRAM RowHammer Vulnerability Profiling Mechanism
Ranyang Zhou, Jacqueline T. Liu, Nakul Kochar +3
RowHammer stands out as a prominent example, potentially the pioneering one, showcasing how a failure mechanism at the circuit level can give rise to a significant and pervasive se…