129 citations · 740 across the 61 of their papers we have counts for
8 papers · 1 filter
UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction
Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif +2
Logic locking aims to prevent intellectual property (IP) piracy and unauthorized overproduction of integrated circuits (ICs). However, initial logic locking techniques were vulnera…
Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework
Muhammad Shafique, Alberto Marchisio, Rachmad Vidya Wicaksana Putra +1
The security and privacy concerns along with the amount of data that is required to be processed on regular basis has pushed processing to the edge of the computing systems. Deploy…
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories
Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
Spiking neural networks (SNNs) have shown a potential for having low energy with unsupervised learning capabilities due to their biologically-inspired computation. However, they ma…
Design and Analysis of High Performance Heterogeneous Block-based Approximate Adders
Ebrahim Farahmand, Ali Mahani, Muhammad Abdullah Hanif +1
Approximate computing is an emerging paradigm to improve the power and performance efficiency of error-resilient applications. As adders are one of the key components in almost all…
Exploiting Vulnerabilities in Deep Neural Networks: Adversarial and Fault-Injection Attacks
Faiq Khalid, Muhammad Abdullah Hanif, Muhammad Shafique
From tiny pacemaker chips to aircraft collision avoidance systems, the state-of-the-art Cyber-Physical Systems (CPS) have increasingly started to rely on Deep Neural Networks (DNNs…
Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks
Khadija Shaheen, Muhammad Abdullah Hanif, Osman Hasan +1
Continual learning is essential for all real-world applications, as frozen pre-trained models cannot effectively deal with non-stationary data distributions. The purpose of this st…
SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM
Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
Spiking Neural Networks (SNNs) have the potential for achieving low energy consumption due to their biologically sparse computation. Several studies have shown that the off-chip me…
DNN-Life: An Energy-Efficient Aging Mitigation Framework for Improving the Lifetime of On-Chip Weight Memories in Deep Neural Network Hardware Architectures
Muhammad Abdullah Hanif, Muhammad Shafique
Negative Biased Temperature Instability (NBTI)-induced aging is one of the critical reliability threats in nano-scale devices. This paper makes the first attempt to study the NBTI…