13 citations · 17 across the 11 of their papers we have counts for
5 papers · 1 filter
ObfusBFA: A Holistic Approach to Safeguarding DNNs from Different Types of Bit-Flip Attacks
Xiaobei Yan, Han Qiu, Tianwei Zhang
Bit-flip attacks (BFAs) represent a serious threat to Deep Neural Networks (DNNs), where flipping a small number of bits in the model parameters or binary code can significantly de…
An Engorgio Prompt Makes Large Language Model Babble on
Jianshuo Dong, Ziyuan Zhang, Qingjie Zhang +7
Auto-regressive large language models (LLMs) have yielded impressive performance in many real-world tasks. However, the new paradigm of these LLMs also exposes novel threats. In th…
Defense against ML-based Power Side-channel Attacks on DNN Accelerators with Adversarial Attacks
Xiaobei Yan, Chip Hong Chang, Tianwei Zhang
Artificial Intelligence (AI) hardware accelerators have been widely adopted to enhance the efficiency of deep learning applications. However, they also raise security concerns rega…
A Unified Hardware-based Threat Detector for AI Accelerators
Xiaobei Yan, Han Qiu, Tianwei Zhang
The proliferation of AI technology gives rise to a variety of security threats, which significantly compromise the confidentiality and integrity of AI models and applications. Exis…
TPU as Cryptographic Accelerator
Rabimba Karanjai, Sangwon Shin, and Wujie Xiong +8
Cryptographic schemes like Fully Homomorphic Encryption (FHE) and Zero-Knowledge Proofs (ZKPs), while offering powerful privacy-preserving capabilities, are often hindered by their…