2 citations · 2 across the 8 of their papers we have counts for
9 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…
Unified Alignment Protocol: Making Sense of the Unlabeled Data in New Domains
Sabbir Ahmed, Mamshad Nayeem Rizve, Abdullah Al Arafat +4
Semi-Supervised Federated Learning (SSFL) is gaining popularity over conventional Federated Learning in many real-world applications. Due to the practical limitation of limited lab…
MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systems
Mohaiminul Al Nahian, Zainab Altaweel, David Reitano +3
Robots need task planning methods to achieve goals that require more than one action. Recently, large pretrained models have demonstrated impressive performance in task planning. F…
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…
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…
DRAM-Locker: A General-Purpose DRAM Protection Mechanism against Adversarial DNN Weight Attacks
Ranyang Zhou, Sabbir Ahmed, Arman Roohi +2
In this work, we propose DRAM-Locker as a robust general-purpose defense mechanism that can protect DRAM against various adversarial Deep Neural Network (DNN) weight attacks affect…
Threshold Breaker: Can Counter-Based RowHammer Prevention Mechanisms Truly Safeguard DRAM?
Ranyang Zhou, Jacqueline Liu, Sabbir Ahmed +3
This paper challenges the existing victim-focused counter-based RowHammer detection mechanisms by experimentally demonstrating a novel multi-sided fault injection attack technique…
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…