SHIELD LAB
Secure and Trustworthy Intelligent Systems Lab
Welcome to Dr. Shahid's SHIELD Lab @ SIUC
How can we harness AI-driven solutions for enhanced security while ensuring they remain secure, trustworthy, and privacy-preserving?
Welcome to the cybersecurity research group at the School of Computing of Southern Illinois University Carbondale, led by Dr. Abdur Rahman Bin Shahid. Our lab is dedicated to pioneering research at the intersection of cybersecurity, AI forensics, and trustworthy AI solutions to address emerging digital threats, privacy challenges, and forensic investigations in AI-driven environments.
Our research spans a diverse array of innovative topics including AI, generative AI forensics, the metaverse, robotics, federated learning, the Internet of Things (IoT), mobile technologies, digital health, interdependent networks, and smart homes.
We leverage AI and emerging technologies to not only enhance the security of cyber-physical and AI-integrated systems but also to develop forensic methodologies for investigating AI-generated threats, ensuring transparency, accountability, and trust in AI applications.
Through interdisciplinary collaborations with renowned experts, industry leaders, and academic partners, we cultivate a dynamic ecosystem of innovation and scholarly exchange. Our ultimate goal is to drive meaningful advancements that redefine the future of CPS, ensuring they are both powerful and protective in our increasingly digital world.
News
March 2025
Three papers have been accepted at the ISARC 2025!
December 2024
Our paper has been accepted at the AAAI PPAI 2025!
October 2024
Our paper has been accepted at the NeurIPS 'GenAI4Health' workshop!
September 2024
Two papers have been accepted at the IEEE ICMLA 2024 conference.
Two research papers have been accepted for poster presentations at IEEE BSN 2024.
The first paper explores the use of Large Language Models (LLMs) in detecting data poisoning attacks, while the second focuses on sponge attacks designed to increase latency and energy consumption in wearable AI devices.
May 2024
Five research papers have been accepted at The IEEE COMPSAC 2024.
Our collaborative research work has been accepted at the IEEE AI-DCS of IEEE ICDCS 2024.
March 2024
Our research on Quantifying Carbon Footprint of Adversarial Machine Learning has been accepted at GreenNet of IEEE ICC 2024.
Secure and Trustworthy Intelligent Systems (SHIELD) Lab
EGRA-409D
1230 Lincoln Dr, Carbondale, IL 62901