University of Ottawa research pushes autonomous security into next-gen networks.
A research team at the University of Ottawa has developed an AI-driven system that can detect and counter wireless jamming attacks in real timea breakthrough that could bolster the reliability and security of critical communications infrastructure. The work, published in the IEEE Internet of Things Journal, aims to address vulnerabilities in modern wireless environments where interference can disrupt everything from emergency response to healthcare and smart city systems.
At its core, the platform uses a dual-agent AI framework that continuously learns to recognise interference patterns and make control decisions fast enough to keep networks functioning even under active jamming. Researchers describe the system as akin to a “digital immune response” for wireless networks, capable of autonomously adapting to dynamic interference without human intervention.
Professor Burak Kantarci, research chair in AI-enabled secure networking at uOttawa, says the two cooperating agents work within Mobile Edge Computing (MEC) and open radio access network (O-RAN) environments to schedule tasks safely when jamming is detected. Early tests showed the system responded robustly across a range of simulated conditions, maintaining continuous connectivity for essential traffic.
The research was conducted over two years by a multidisciplinary team including PhD student Ghazal Asemian and Dr Iman Amini, with support from Canadian spectrum intelligence firm thinkRF. According to industry partners, integrating autonomous detection and mitigation directly into network control loops is increasingly seen as necessary as wireless infrastructure becomes both more complex and more mission-critical.
Jamming attacksintentional efforts to interfere with radio frequency signals have grown in both accessibility and frequency. Traditional countermeasures rely on static defenses that struggle with modern adaptive threats; AI-based real-time approaches promise more resilient operation without manual tuning.
Experts say this research complements wider trends where AI is embedded deeper into wireless systems from predictive resource allocation to autonomous spectrum management which are essential components of future 5G-Advanced and 6G networks. Broader industry alliances and AI-native radio access efforts continue to push the sector toward networks that can self-optimize and defend against evolving threats.
