1 citations · 1 across the 7 of their papers we have counts for
7 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…
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…
Attacks on Continuous Chaos Communication and Remedies for Resource Limited Devices
Rahul Vishwakarma, Ravi Monani, Amin Rezaei +3
The Global Wearable market is anticipated to rise at a considerable rate in the next coming years and communication is a fundamental block in any wearable device. In communication,…
Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design
Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi +6
The emergence of High-Level Synthesis (HLS) tools shifted the paradigm of hardware design by making the process of mapping high-level programming languages to hardware design such…
Energy-Efficiency Prediction of Multithreaded Workloads on Heterogeneous Composite Cores Architectures using Machine Learning Techniques
Hossein Sayadi
Heterogeneous architectures have emerged as a promising alternative for homogeneous architectures to improve the energy-efficiency of computer systems. Composite Cores Architecture…