Dr. Hadis Karimipour is the director of SCPS Lab and an Assistant Professor in the School of Engineering at the University of Guelph. Her research mainly focuses on the application of Artificial Intelligent (AI) and machine learning on the Internet of Things (IoT) and critical infrastructure security. Read more...
Her research interest includes:
Her research interest includes:
- AI-enabled IoT Security
- Security of Critical Cyber-physical System
- Machine Learning/Deep Learning
- Monitoring and Control of Smart Grids
- Sept. 1- Our paper “A Hybrid Deep Learning-Based State Forecasting Method for Smart Power Grids” is accepted paper for presentation at IEEE System, Men, Cybernetic (IEEE SMC 2020)
- Aug. 25- Our paper “Real-time Stability Assessment in Smart Cyber-physical Grids: A Deep Learning Approach” is published IET Smart Grid Journal.
- Aug. 18- Our paper “Ensemble Sparse Representation-based Cyber Threat Hunting for Security of Smart Cities” is published at Elsevier Computers & Electrical Engineering Journal
- Aug. 10- Our paper “Enabling Drones in the Internet of Things with Decentralized Blockchain-based Security” is published at IEEE Internet of Things Journal
- July 23- Our book on “Security of Cyber-Physical Systems: Vulnerability and Impact” is published at Springer, Cham.
- June 15- Our paper “An Energy Efficient Artificial Bee Colony-based Clustering in the Internet of Things” is published at Elsevier Computer & Electrical Engineering Journal
- May 13- Our paper “An Ensemble Deep Learning-Based Cyber-Attack Detection in Industrial Control System” is published at IEEE Access Journal
- May 8 - Congratulation to Jacob on his successful MASc. defense.
- April 17- Our paper “A Deep Neural Network Combined with Radial Basis Function for Abnormality Classification” is accepted for publication in Mobile Networks and Applications Journal.
- Feb 25- Our paper “An Improved Two Hidden-layer Extreme Learning Machine for Malware Hunting” is published at Elsevier Computer & Security Journal.
- Feb 1- Our paper “Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey” is published at Elsevier Journal of Network and Computer Applications.
- Jan 21- Our paper “Detecting Cryptomining Malware: A Deep Learning Approach for Static and Dynamic Analysis” is published at Journal of Grid Computing.
Available MASc and PHD Position (AI Stream)
Artificial Intelligence for Protecting Critical Infrastructure
Although the digitalization of Critical Infrastructures (CI) through the Internet of Things (IoT) facilitates real-time monitoring and control of these systems, it presents an array of complex security and monitoring challenges to CI. The backbone of these facilities, including oil and gas, refinery, and smart grids, consists of an Industrial Control System (ICS). A cyber-attack/ fault on ICS will result in anomalous process/network behavior, which should be identified in a timely manner to prevent catastrophic damages.
This project is focused on building a multi-view Deep Learning (DL) anomaly detection model designed explicitly for threat hunting in ICS.
For more information please visit Future Students page.