3 citations · 4 across the 19 of their papers we have counts for
19 papers
Digital Twin-Based Intrusion Detection for Vehicle Powertrain CAN Bus Systems
Araf Rahman, M Sabbir Salek, Mashrur Chowdhury
Existing automotive intrusion detection systems (IDSs) for the Controller Area Network (CAN) largely target discrepancies in message timing, frequency, or sequencing and cannot det…
Structured Driving-State Narratives for Small Language Model-Based GNSS Spoofing Detection
Abyad Enan, Sagar Dasgupta, Mizanur Rahman +1
Autonomous vehicles (AVs) depend on reliable Global Navigation Satellite System (GNSS) positioning. However, spoofed GNSS signals can induce plausible but incorrect vehicle states.…
Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems
Mohammad Imtiaz Hasan, M Sabbir Salek, Nathan Jones +2
By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve road safety. However, adversaries…
Development of Vision-Language Model-based GNSS Spoofing Detection for Autonomous Vehicle Navigation
Mohammed Aldeen, Muhammad Sami Irfan, Sagar Dasgupta +3
Autonomous vehicles (AVs) depend on Global Navigation Satellite Systems (GNSS) for localization and navigation, making them vulnerable to spoofing attacks that can covertly redirec…
In-Vehicle Digital Twin-Based Collision Warning Framework with Sybil Attack Detection
Mohammad Imtiaz Hasan, Abyad Enan, Jean Michel Tine +3
Connected Vehicles (CVs) rely extensively on communication technologies to enable data-driven predictive analyses for enhancing performance and safety. These communication channels…
Evaluating the Impact of Adversarial Attacks on Traffic Sign Classification using the LISA Dataset
Nabeyou Tadessa, Balaji Iyangar, Mashrur Chowdhury
Adversarial attacks pose significant threats to machine learning models by introducing carefully crafted perturbations that cause misclassification. While prior work has primarily…
DisPatch: Disarming Adversarial Patches in Object Detection with Diffusion Models
Jin Ma, Mohammed Aldeen, Christopher Salas +4
Object detection is fundamental to various real-world applications, such as security monitoring and surveillance video analysis. Despite their advancements, state-of-the-art object…
Precision-Aware Video Compression for Reducing Bandwidth Requirements in Video Communication for Vehicle Detection-Based Applications
Abyad Enan, Jon C Calhoun, Mashrur Chowdhury
Computer vision has become a popular tool in intelligent transportation systems (ITS), enabling various applications through roadside traffic cameras that capture video and transmi…
Real-Time Conflict Prediction for Large Truck Merging in Mixed Traffic at Work Zone Lane Closures
Abyad Enan, Abdullah Al Mamun, Gurcan Comert +4
Large trucks substantially contribute to work zone-related crashes, primarily due to their large size and blind spots. When approaching a work zone, large trucks often need to merg…
Real-World Evaluation of Protocol-Compliant Denial-of-Service Attacks on C-V2X-based Forward Collision Warning Systems
Jean Michel Tine, Mohammed Aldeen, Abyad Enan +3
Cellular Vehicle-to-Everything (C-V2X) technology enables low-latency, reliable communications essential for safety applications such as a Forward Collision Warning (FCW) system. C…
Understanding the Risks of Asphalt Art to the Reliability of Vision-Based Perception Systems
Jin Ma, Abyad Enan, Long Cheng +1
Artistic crosswalks featuring asphalt art, introduced by different organizations in recent years, aim to enhance the visibility and safety of pedestrians. However, their visual com…
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign Classification
Reek Majumder, Mashrur Chowdhury, Sakib Mahmud Khan +6
Deep learning (DL)-based image classification models are essential for autonomous vehicle (AV) perception modules since incorrect categorization might have severe repercussions. Ad…
GAN-Based Single-Stage Defense for Traffic Sign Classification Under Adversarial Patch
Abyad Enan, Mashrur Chowdhury
Computer vision plays a critical role in ensuring the safe navigation of autonomous vehicles (AVs). An AV perception module facilitates safe navigation. This module enables AVs to…
Quantum-Inspired Weight-Constrained Neural Network: Reducing Variable Numbers by 100x Compared to Standard Neural Networks
Shaozhi Li, M Sabbir Salek, Mashrur Chowdhury +1
Although quantum machine learning has shown great promise, the practical application of quantum computers remains constrained in the noisy intermediate-scale quantum era. To take a…
Quantum Annealing-Enhanced Virtual Traffic Lights and its Evaluation Using a Quantum-in-the-Loop Simulation Testbed
Abyad Enan, M Sabbir Salek, Mashrur Chowdhury +3
Virtual Traffic Light (VTL) is a traffic control method that does not require traffic signal-related infrastructure for roadway intersections. Connected vehicles (CVs) are given ri…
Quantum-inspired activation functions and quantum Chebyshev-polynomial network
Shaozhi Li, M Sabbir Salek, Yao Wang +1
Driven by the significant advantages offered by quantum computing, research in quantum machine learning has increased in recent years. While quantum speed-up has been demonstrated…
An Overview of Automated Vehicle Longitudinal Platoon Formation Strategies
M Sabbir Salek, Mugdha Basu Thakur, Pardha Sai Krishna Ala +5
Automated vehicle (AV) platooning has the potential to improve the safety, operational, and energy efficiency of surface transportation systems by limiting or eliminating human inv…
Leveraging Public Cloud Infrastructure for Real-time Connected Vehicle Speed Advisory at a Signalized Corridor
Hsien-Wen Deng, M Sabbir Salek, Mizanur Rahman +3
In this study, we developed a real-time connected vehicle (CV) speed advisory application that uses public cloud services and tested it on a simulated signalized corridor for diffe…
AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles
M Sabbir Salek, Abdullah Al Mamun, Mashrur Chowdhury
This study developed a generative adversarial network (GAN)-based defense method for traffic sign classification in an autonomous vehicle (AV), referred to as the attack-resilient…