5 papers
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…
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…
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…