Clavister Wins project with Swedish Defence Forces and Swedish Innovation Agency
Örnsköldsvik, Sweden - 31 October 2024 - Clavister, a leader in European cybersecurity for mission-critical applications, announced today that it has been awarded a research project by the Swedish Defence Forces and the Swedish Innovation Agency on AI technologies for drone operations.
The new research project aims at enabling drone operations and increase their survivability through AI-powered cybersecurity in jammed radio environments, like the ones being reported from Ukraine.
The project is funded through a joint program between the Swedish Innovation Agency (Vinnova) and the Swedish Defence Forces (Försvarsmakten) called “Collaborative project for civil-military synergies”, with a focus on leveraging dual use technologies. The project will be delivered by Clavister in cooperation with the Swedish company Wireless P2P Technologies AB.
Clavister will study advanced AI methods for jamming detection on-board drones, leveraging Clavister’s proprietary AI technology and experience from previous research and commercial projects. The project will involve studies and field testing using an existing cognitive radio platform based on Software-Defined Radio (SDR) provided by the project partner Wireless P2P Technologies.
“I’m happy that we can contribute to solving very urgent defence challenges by leveraging our technology and experience, both from civilian and military domains. We continue to find new use cases for our patented AI technology, and by working with domain experts like Wireless P2P Technologies we can add value to new domains where cybersecurity is gaining importance,” comments John Vestberg, CEO of Clavister.
The increasing use of drones in modern conflicts is accompanied by a rise in countermeasures like radio jamming, also referred to Electromagnetic Warfare (EW), creating challenges in remote control and data transmission which can cause the drones to crash. To effectively utilise allocated RF resources, drones must be capable of spectrum monitoring in complex operational environments, particularly by detecting intentional jamming of the frequencies they rely on.
The project will explore the application of advanced AI/ML algorithms to detect intentional jamming from technically skilled adversaries. The focus is on equipping drone users with advanced detection and identification capabilities to reduce drone losses and enhance situational awareness in the electromagnetic domain by mapping adversarial jammers. Through these capabilities, drones can better navigate contested RF environments, thereby improving operational effectiveness and resilience in modern warfare.