Anomaly Detection on Serial Bus Systems (extension)

Thales, a global leader in technology, invests in digital and “deep tech” innovations such as Big Data, artificial intelligence, connectivity, cybersecurity, and quantum technology to create a trustworthy future. Operating across defense and security, aerospace, digital identity and security, and transport, Thales delivers solutions, services, and products that support critical missions. This internship falls under the Serial Heckler initiative, which aims to enhance the safety of vehicular platforms by securing the CAN Bus.
The project will utilize machine learning to manage high-dimensional, high-frequency data, tackle class imbalance with infrequent anomalies, and pioneer feature engineering techniques to detect subtle discrepancies in vehicular communications—all while ensuring real-time processing for robust cybersecurity. Additionally, the intern will incorporate advanced algorithmic strategies that optimize detection accuracy by analyzing patterns over time and across various system inputs, without relying on continuous manual updates or intervention.
Thales collaborates closely with Canadian public safety organizations such as the Canadian Space Agency or Defence Research and Development Canada, for making any advancements achieved by Thales a direct benefit to Canada. The success of this project not only benefits Thales but also strengthens Canada’s position at the forefront of innovation and technological development in crucial domains.

Faculty Supervisor:

Omar Abdul Wahab;Adel Abusitta

Student:

Partner:

Thales Recherche et Technologie

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program: