Intrusion Detection System for the Internet of Things Intrusion Detection System for the Internet of Things

Vasos Vassiliou, Associate Professor, Research Group Leader, CYENS Centre of Excellence
/ Department of Computer Science,
University of Cyprus
Christis Christophorou, IT Professional and Business Consultant, CYENS Centre of Excellence
Christiana Ioannou, PhD, Research Fellow
, CYENS Centre of Excellence

The Internet of Things (IoT) may be the most insecure type of network. Each IoT system is designed for a specific purpose and environmental setting, making it challenging to apply standardised security measures.

When an organisation looks at creating, deploying, and leveraging IoT technology to drive its business, security must be integrated into every component to minimise the risk of cyber-threats. offers a set of intelligent algorithms that enable Home and Industrial IoT networks to recognise intrusions and anomalies in their operation. captures data on the overall state of an IoT system, including endpoint and connectivity traffic, and its algorithms automate the process of analysing network (IT) and operational (OT) data.

Using various Machine Learning and Computational Intelligence techniques, examines the network and application, recognises anomalous behaviour and offers attack, misuse, malfunction, or failure detection. envisions becoming a B2B cybersecurity insights provider in the IoT Platforms ecosystem globally.