AI-driven cybersecurity for IoT and cloud infrastructures - ON-1125

Genre de projet: Innovation
Discipline(s) souhaitée(s): Génie - informatique / électrique, Génie, Informatique, Sciences mathématiques
Entreprise: TAC SECURITY (CANADA) INC.
Durée du projet: 6 mois à 1 an
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): Toronto, ON, Canada; Canada
Nombre de postes: 2-3
Niveau de scolarité désiré: MaîtriseDoctoratRecherche postdoctorale
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: No

Au sujet de l’entreprise: 

TAC Security is a global leader in cybersecurity solutions with operations in India, the USA, and now Canada. Our Canadian subsidiary focuses on advancing research and innovation in threat management, vulnerability assessment, and IoT/Cloud security. We work with government, BFSI, and enterprise clients to secure mission-critical infrastructure. Our team combines deep technical expertise with strategic leadership across product development, auditing, operations, and business expansion.

The Toronto-based subsidiary will serve as a hub for research and innovation, collaborating with Canadian universities and talent on advanced cybersecurity technologies. We are committed to mentoring the next generation of cybersecurity leaders while developing cutting-edge products that enhance digital trust and resilience.

TAC Security (Canada) is actively building its leadership and operations team in Canada. Senior professionals (VP Product, VP Business, Head of Operations, Lead Auditors, Engineers) will provide mentorship and guidance to Mitacs interns, ensuring they gain hands-on exposure to both technical research and applied innovation in the cybersecurity industry.

Veuillez décrire le projet.: 

This project aims to develop an AI-driven cybersecurity framework to protect IoT devices and cloud-based infrastructures from evolving threats. The increasing use of connected devices in critical sectors (finance, government, and smart cities) creates vast attack surfaces that traditional security tools cannot adequately protect.

The R&D focus will be on:
• Building machine learning models for anomaly detection and predictive threat intelligence.
• Developing automated vulnerability assessment workflows for IoT devices.
• Enhancing secure communication protocols using cryptography and blockchain-based validation.
• Creating dashboards and visualization tools for real-time monitoring and reporting.

Interns will support algorithm design, penetration testing, and integration of research into a working prototype. They will gain experience with secure coding practices, cloud-native environments, and applied cybersecurity tools. The project outputs will directly feed into TAC Security’s product roadmap, accelerating our innovation cycle while contributing to academic knowledge in cybersecurity.

Expertise ou compétences exigées: 

• Strong foundation in cybersecurity, computer science, or software engineering.
• Experience in AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Knowledge of IoT protocols, cryptography, and cloud platforms (AWS/Azure).
• Familiarity with penetration testing tools (Burp Suite, Nmap, Nessus).
• Programming skills: Python, Node.js, or Java.
• Bonus: prior research experience in anomaly detection, blockchain, or threat intelligence.