Emergence of IoT devices and applications, introduced many new challenges for cybersecurity community. Cyber Science Lab has an extensive research track in IoT/ICS network defense, AI-aided attack detection and analysis in IoT networks and IoT digital investigation. (for more information please see our latest publications[AD3] ):
o Security of Smart Grids: The fast adoption of smart devices and integration with cloud computing and other classic IT networks has significantly increased the number and sophistication of attacks applicable to smart grids. The sheer volume, veracity, and velocity of data exchange in smart grid networks render traditional manual and human-oriented cybersecurity defense techniques impractical and ineffective. In this project, the Cyber Science Lab at the University of Guelph builds an integrated OT (operational technology) – IT (information technology) machine learning-based cyber threat hunting, intelligence, and attack prediction systems for smart grids. The system is capable of identifying characteristics of a threat hunting task in smart grid, to specify events of interest and to create a practical format for Indications of Compromise (IoCs) and Indications of Attacks (IoAs) in smart grids. The system contains an ML-stack with agents that can share their learning space for optimal real-time threat hunting over sizable data with different formats. The threat intelligence system is capable of creating, sharing and consuming threat feeds that contain observables from various combinations of measurements through advanced metering infrastructure (AMI), states, and control actions (i.e. voltage, frequency, etc.).
o Security of Smart Agriculture Systems(Download Report): Smart systems and robots are poised to play a key role in farming and agriculture, fueling the success of the Third Green Revolution and improving worldwide food security. However, cybersecurity of these internet-connected systems threaten the adoption of these systems by farmers. In an assessment made by Canada Digital Agri-Food (CDAF), farmers’ primary concerns included having people hack into their systems to collect data for nefarious reasons or to sabotage their farms’ environmental controls. In this project, we conducted a study to understand and identify the potential market opportunity for the Cybersecurity for Protecting Smart & Precision Farming technology in greater detail, and to validate the value proposition with industry key opinion leaders/stakeholders.