Adversarially Resilient Federated Learning for Intrusion Detection in 5G Networks

This project will design and test a new privacy-preserving, attack-resilient cybersecurity system for 5G networks using Federated Learning (FL), an approach where multiple devices can train models together without sharing sensitive data. The goal is to improve protection against cyberattacks such as denial-of-service and model poisoning, which threaten the reliability of modern mobile services like […]

Read More
L2M – AI-Driven Cybersecurity for Ocean Critical Infrastructure

This project will develop an AI-powered cybersecurity system to help protect important ocean infrastructure, starting with offshore energy systems such as oil and gas, wind and tidal farms. These facilities are becoming a key part of Canada’s clean energy future but are also vulnerable to cyberattacks that could cause costly shutdowns or disruptions. The project […]

Read More
Adaptive Human–LLM Teaming for Scalable Cybersecurity at eSentire

This project will explore how AI can best complement human expertise in cybersecurity operations. The intern will collaborate with industry professionals at eSentire to study how tasks are currently performed, develop lightweight AI-based tools to support key workflows, and design a method to assess the impact of these tools in real-world conditions. The goal is […]

Read More
L2M Validation / Qc Automne 2025 / Sécurisation des ordinateurs quantiques contre des cybermenaces

La concrétisation des ordinateurs quantiques introduit de nouveaux vecteurs d’attaque tels que les virus quantiques, les cyberattaques quantiques. Les outils actuels de détection des virus informatiques ou des menaces cyber n’ont pas été conçus pour les ordinateurs quantiques, les exposant ainsi à des nouvelles vulnérabilités qui peuvent être exploitées par les acteurs malicieux. Les fournisseurs […]

Read More
L2M Validation / Qc Automne 2025 / AuthoMate

Les organisations canadiennes des secteurs financier, santé et cloud subissent d’énormes pertes économiques dues aux limitations des systèmes de contrôle d’accès actuels qui présentent des insuffisances majeures : incapacité à gérer simultanément les contraintes temporelles, historiques et contextuelles, vulnérabilités aux erreurs de configuration causant des violations de données (coûtant 6,32 M$ CAD par incident), et […]

Read More
Enhancing Privacy Against Surveillance and Censorship in Future Internet Architectures

The dramatic growth of the Internet has enhanced access to information, fostering seamless communication and promoting effective collaboration. Unfortunately, advanced network traffic control and monitoring systems have empowered state-level actors to deploy large-scale surveillance and censorship mechanisms that track people’s Internet activities or limit their ability to freely access and publish information. Recently, multiple initiatives […]

Read More
L2M QC Spring 2025 | Tools for the automation of auditing of smart contracts for blockchain applications

The increasing adoption of blockchain technology, particularly in decentralized finance (DeFi), highlights the critical need for automated and efficient auditing tools for smart contracts and transaction monitoring. Traditional manual auditing methods are slow, labor-intensive, and insufficient to manage the growing complexity of smart contracts. By integrating AI-based techniques, this project aims to develop automated tools […]

Read More
Improved Order Computation in Class Groups of Real Quadratic Fields

Cryptography is an important tool for safeguarding our data from attackers. The security of several modern cryptosystems relies on unproven properties of an algebraic structure called the class group of an algebraic number field. In the absence of proofs, tabulating class groups in order to generate numerical evidence of these unproven properties remains the best […]

Read More
L2M – Study for the Smart Risk Assessment & Micro-Segmentation of Networks

This project aims to develop an innovative and novel cybersecurity solution tailored for Canadian small and medium-sized enterprises (SMEs), focusing on smart risk assessment and automated network segmentation. Many SMEs lack full visibility into their IT infrastructure, leaving them vulnerable to cyber threats. This project will study the challenges and needs of SMEs across different […]

Read More
L2M QC Spring 2025 | Robust THz technology for efficient and secured data exchange

The surge in data driven by economic expansion has increased the demand for fast, reliable internet. However, existing technologies struggle to keep up, causing video buffering, game lag, and slow file transfers. At the same time, rising cyber threats make data security a top concern, with high-profile breaches compromising millions of users and causing financial […]

Read More