As malicious malware attacks on IoT devices continue to rise, the need for effective detection solutions is critical. While considerable research has focused on traditional devices like PCs and smartphones, those approaches don’t translate well to IoT devices, such as medical equipment, smart home components, autonomous vehicles, and industrial systems, which are diverse and have limited computing power. Additionally, current detection models face difficulties in identifying more sophisticated malware.

Together with Rochester Institute of Technology (RIT), University of Buffalo (UB), and University College Cork (UCC), Queen’s researchers will develop a new IoT malware detection method that is universal, efficient, and robust. 

Dr Niall McLaughlin and Professor Paul Miller, based at Queen’s, are part of the multi-institution research team utilising artificial intelligence (AI) to improve malware detection across IoT devices that could lead to safer airports, factories and connected homes.

Dr Niall McLaughlin, based at The Centre for Secure Information Technologies (CSIT) at Queen’s, commented:

“We are delighted to be collaborating with RIT, UB, and UCC to deliver a reliable and scalable solution for detecting malware on IoT devices. This proposed new method has the potential to truly transform the security of these devices and make the world around us safer.”

The US-Ireland R&D Partnership is a tri-jurisdictional alliance which supports collaborative research with the potential to generate valuable discoveries and innovations which are transferable to the marketplace.

Professor Paul Miller, Deputy Director at CSIT, added:

“Cross-collaboration between institutions through the US-Ireland R&D Partnership Programme brings together diverse expertise and perspectives that are essential for tackling complex challenges like IoT security. By pooling our knowledge and resources, we can drive innovation more effectively and develop solutions that have a real-world impact on global cyber security.”

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Contact Helen Lappin for further information.