Driving cybersecurity solutions for smart transportation systems
Transportation technology is shifting gears towards turning streets into networks of connected and autonomous vehicles and intelligent traffic systems. At Ryerson’s Laboratory of Innovations in Transportation Lab, external link (LiTrans Lab), researchers are developing solutions to protect the smart systems that are the future of transportation, from vulnerabilities that could result in traffic disruptions to privacy breaches.
Engineering professor and Canada Research Chair in Disruptive Transportation Technologies and Services Bilal Farooq and his team at LiTrans are researching solutions to address the potential cybersecurity vulnerabilities in smart and adaptive traffic systems. The lab has developed digital defences in the form of game theory and reinforcement learning-based solutions to counter a type of distributed attack, known as a Sybil attack, that could cause disruptions in connected traffic flow.
Traffic disruptions aren’t the only cybersecurity concern when it comes to the future of transportation. Federated machine learning is a tool that can be used to protect the privacy of citizen information while creating machine learning models that can be used to build better smart mobility and smart city systems. LiTrans has created a blockchain-based solution for the detection and neutralization of possible attempts by a malicious actor to inject bad data into a model’s learning pool to hinder training.
Finally, the lab has developed the Blockchain-based Smart Mobility Data-market (BSMD) platform to address cybersecurity and privacy concerns around people’s data. Without a cybersecurity solution, people’s identities, activities, preferences and movement patterns could potentially be breached. The BSMD platform would give users more control and protection of their data, allowing them to choose with whom they share information like their location or movement habits and preferences.