19 citations · 31 across the 7 of their papers we have counts for
9 papers
Is Mamba Reliable for Medical Imaging?
Banafsheh Saber Latibari, Najmeh Nazari, Daniel Brignac +3
State-space models like Mamba offer linear-time sequence processing and low memory, making them attractive for medical imaging. However, their robustness under realistic software a…
Bit of a Close Talker: A Practical Guide to Serverless Cloud Co-Location Attacks
Wei Shao, Najmeh Nazari, Behnam Omidi +4
Serverless computing has revolutionized cloud computing by offering users an efficient, cost-effective way to develop and deploy applications without managing infrastructure detail…
FaRAccel: FPGA-Accelerated Defense Architecture for Efficient Bit-Flip Attack Resilience in Transformer Models
Najmeh Nazari, Banafsheh Saber Latibari, Elahe Hosseini +8
Forget and Rewire (FaR) methodology has demonstrated strong resilience against Bit-Flip Attacks (BFAs) on Transformer-based models by obfuscating critical parameters through dynami…
Hammering the Diagnosis: Rowhammer-Induced Stealthy Trojan Attacks on ViT-Based Medical Imaging
Banafsheh Saber Latibari, Najmeh Nazari, Hossein Sayadi +2
Vision Transformers (ViTs) have emerged as powerful architectures in medical image analysis, excelling in tasks such as disease detection, segmentation, and classification. However…
Transformers for Secure Hardware Systems: Applications, Challenges, and Outlook
Banafsheh Saber Latibari, Najmeh Nazari, Avesta Sasan +4
The rise of hardware-level security threats, such as side-channel attacks, hardware Trojans, and firmware vulnerabilities, demands advanced detection mechanisms that are more intel…
Automated Hardware Logic Obfuscation Framework Using GPT
Banafsheh Saber Latibari, Sujan Ghimire, Muhtasim Alam Chowdhury +5
Obfuscation stands as a promising solution for safeguarding hardware intellectual property (IP) against a spectrum of threats including reverse engineering, IP piracy, and tamperin…
Large Language Models for Code Analysis: Do LLMs Really Do Their Job?
Chongzhou Fang, Ning Miao, Shaurya Srivastav +8
Large language models (LLMs) have demonstrated significant potential in the realm of natural language understanding and programming code processing tasks. Their capacity to compreh…
Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks
Chongzhou Fang, Han Wang, Najmeh Nazari +5
Cloud computing paradigms have emerged as a major facility to store and process the massive data produced by various business units, public organizations, Internet-of-Things, and c…
Multi-level Binarized LSTM in EEG Classification for Wearable Devices
Najmeh Nazari, Seyed Ahmad Mirsalari, Sima Sinaei +2
Long Short-Term Memory (LSTM) is widely used in various sequential applications. Complex LSTMs could be hardly deployed on wearable and resourced-limited devices due to the huge am…