1 citations · 1 across the 3 of their papers we have counts for
5 papers
TEE-X: TEE-aware Acceleration Framework for Large Vision Models at the Edge
Kurt M Wilson, Mohaiminul Al Nahian, Abeer Matar A. Almalky +5
Despite their remarkable success, machine learning models, particularly in vision applications, are alarmingly vulnerable to a range of security threats. One key factor in the atta…
PROTEA: Securing Robot Task Planning and Execution
Zainab Altaweel, Mohaiminul Al Nahian, Jake Juettner +2
Robots need task planning methods to generate action sequences for complex tasks. Recent work on adversarial attacks has revealed significant vulnerabilities in existing robot task…
Invisible Hands: Gray-Box Bit Flip Attack for Steering LLMs Without Knowledge of Gradients, Data, and Weights
Abeer Matar A. Almalky, Ziyan Wang, Mohaiminul Al Nahian +2
In recent years, large language models (LLMs) have achieved remarkable advances and are increasingly deployed in critical applications across diverse domains. This growing adoption…
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…
CNN-Based Prediction of Frame-Level Shot Importance for Video Summarization
Mohaiminul Al Nahian, A. S. M. Iftekhar, Mohammad Tariqul Islam +2
In the Internet, ubiquitous presence of redundant, unedited, raw videos has made video summarization an important problem. Traditional methods of video summarization employ a heuri…