65 citations · 93 across the 21 of their papers we have counts for
23 papers
RampoNN: A Reachability-Guided System Falsification for Efficient Cyber-Kinetic Vulnerability Detection
Kohei Tsujio, Mohammad Abdullah Al Faruque, Yasser Shoukry
Detecting kinetic vulnerabilities in Cyber-Physical Systems (CPS), vulnerabilities in control code that can precipitate hazardous physical consequences, is a critical challenge. Th…
LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
Mohamad Fakih, Rahul Dharmaji, Halima Bouzidi +3
Software vulnerabilities continue to be ubiquitous, even in the era of AI-powered code assistants, advanced static analysis tools, and the adoption of extensive testing frameworks.…
Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception
Mohanad Odema, Luke Chen, Hyoukjun Kwon +1
We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems…
LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems
Mohamad Fakih, Rahul Dharmaji, Yasamin Moghaddas +3
Although Large Language Models (LLMs) have established pre-dominance in automated code generation, they are not devoid of shortcomings. The pertinent issues primarily relate to the…
RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding
Junyao Wang, Arnav Vaibhav Malawade, Junhong Zhou +2
Effectively capturing intricate interactions among road users is of critical importance to achieving safe navigation for autonomous vehicles. While graph learning (GL) has emerged…
CFG2VEC: Hierarchical Graph Neural Network for Cross-Architectural Software Reverse Engineering
Shih-Yuan Yu, Yonatan Gizachew Achamyeleh, Chonghan Wang +3
Mission-critical embedded software is critical to our society's infrastructure but can be subject to new security vulnerabilities as technology advances. When security issues arise…
BayesImposter: Bayesian Estimation Based .bss Imposter Attack on Industrial Control Systems
Anomadarshi Barua, Lelin Pan, Mohammad Abdullah Al Faruque
Over the last six years, several papers used memory deduplication to trigger various security issues, such as leaking heap-address and causing bit-flip in the physical memory. The…
Neural Contextual Bandits Based Dynamic Sensor Selection for Low-Power Body-Area Networks
Berken Utku Demirel, Luke Chen, Mohammad Abdullah Al Faruque
Providing health monitoring devices with machine intelligence is important for enabling automatic mobile healthcare applications. However, this brings additional challenges due to…
SELF-CARE: Selective Fusion with Context-Aware Low-Power Edge Computing for Stress Detection
Nafiul Rashid, Trier Mortlock, Mohammad Abdullah Al Faruque
Detecting human stress levels and emotional states with physiological body-worn sensors is a complex task, but one with many health-related benefits. Robustness to sensor measureme…
Hardware Trojan Detection using Graph Neural Networks
Rozhin Yasaei, Luke Chen, Shih-Yuan Yu +1
The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third…
HydraFusion: Context-Aware Selective Sensor Fusion for Robust and Efficient Autonomous Vehicle Perception
Arnav Vaibhav Malawade, Trier Mortlock, Mohammad Abdullah Al Faruque
Although autonomous vehicles (AVs) are expected to revolutionize transportation, robust perception across a wide range of driving contexts remains a significant challenge. Techniqu…
Future of Smart Classroom in the Era of Wearable Neurotechnology
Mojtaba Taherisadr, Berken Utku Demirel, Mohammad Abdullah Al Faruque +1
Interdisciplinary research among engineering, computer science, and neuroscience to understand and utilize the human brain signals resulted in advances and widespread applicability…
Multi-Modal Attack Detection for Cyber-Physical Additive Manufacturing
Shih-Yuan Yu, Arnav Vaibhav Malawade, Mohammad Abdullah Al Faruque
Cyber-Physical Additive Manufacturing (AM) constructs a physical 3D object layer-by-layer according to its digital representation and has been vastly applied to fast prototyping an…
Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor
Nafiul Rashid, Luke Chen, Manik Dautta +3
Stress is a physiological state that hampers mental health and has serious consequences to physical health. Moreover, the COVID-19 pandemic has increased stress levels among people…
Energy-efficient Blood Pressure Monitoring based on Single-site Photoplethysmogram on Wearable Devices
Wenrui Lin, Berken Utku Demirel, Mohammad Abdullah Al Faruque +1
The paper proposes accurate Blood Pressure Monitoring (BPM) based on a single-site Photoplethysmographic (PPG) sensor and provides an energy-efficient solution on edge cuffless wea…
Single-Channel EEG Based Arousal Level Estimation Using Multitaper Spectrum Estimation at Low-Power Wearable Devices
Berken Utku Demirel, Ivan Skelin, Haoxin Zhang +2
This paper proposes a novel lightweight method using the multitaper power spectrum to estimate arousal levels at wearable devices. We show that the spectral slope (1/f) of the elec…
HW2VEC: A Graph Learning Tool for Automating Hardware Security
Shih-Yuan Yu, Rozhin Yasaei, Qingrong Zhou +2
The time-to-market pressure and continuous growing complexity of hardware designs have promoted the globalization of the Integrated Circuit (IC) supply chain. However, such globali…
Establishing Digital Recognition and Identification of Microscopic Objects for Implementation of Artificial Intelligence (AI) Guided Microassembly
Tuo Zhou, Shih-Yuan Yu, Matthew Michaels +3
s miniaturization of electrical and mechanical components used in modern technology progresses, there is an increasing need for high-throughput and low-cost micro-scale assembly te…
LENS: Layer Distribution Enabled Neural Architecture Search in Edge-Cloud Hierarchies
Mohanad Odema, Nafiul Rashid, Berken Utku Demirel +1
Edge-Cloud hierarchical systems employing intelligence through Deep Neural Networks (DNNs) endure the dilemma of workload distribution within them. Previous solutions proposed to d…
GNN4IP: Graph Neural Network for Hardware Intellectual Property Piracy Detection
Rozhin Yasaei, Shih-Yuan Yu, Emad Kasaeyan Naeini +1
Aggressive time-to-market constraints and enormous hardware design and fabrication costs have pushed the semiconductor industry toward hardware Intellectual Properties (IP) core de…
Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions
Shih-Yuan Yu, Arnav V. Malawade, Deepan Muthirayan +2
Despite impressive advancements in Autonomous Driving Systems (ADS), navigation in complex road conditions remains a challenging problem. There is considerable evidence that evalua…
Pykg2vec: A Python Library for Knowledge Graph Embedding
Shih Yuan Yu, Sujit Rokka Chhetri, Arquimedes Canedo +2
Pykg2vec is an open-source Python library for learning the representations of the entities and relations in knowledge graphs. Pykg2vec's flexible and modular software architecture…
Future Automation Engineering using Structural Graph Convolutional Neural Networks
Jiang Wan, Blake S. Pollard, Sujit Rokka Chhetri +3
The digitalization of automation engineering generates large quantities of engineering data that is interlinked in knowledge graphs. Classifying and clustering subgraphs according…