Cyber attacks have become more widespread and several attacks have made headline news over the past decade, targeting industrial companies and governmental organizations. These attacks have caused substantial financial losses and were able to hinder the operation of core public services. Furthermore, since the Internet of Things (IoT) has emerged, the number of devices connected to the Internet is increasing rapidly and becoming easy targets for cyber attacks. To mitigate cyber attacks, cyber security analysts heavily depend on Intrusion Detection Systems (IDSs) which can detect malicious activities by matching patterns of known attacks (i.e. signature-based) or observing anomaly activities (i.e. anomaly-based).
This project aims to tackle Trust, Identity, Privacy and Security (TIPS) issues in large-scale networks and Internet of Things. The proposed research aims at developing a practically deployable cyber security solution to one or more of the cyber attacks. Multi-Stage Attacks (MSAs), Advanced Persistent Threats (APTs), Denial of Service (DoS) attacks, wireless injection attacks, botnets or other malicious activities will be investigated. The developed algorithms would be based on advanced Artificial Intelligence (AI) technologies. Network security monitor tools will be used to analyse the network traffic and a novel IDS will be developed using machine learning algorithms.
· Master’s degree in Computer Science or related disciplines such as Information Security, Cyber Security, Computer Networks, Artificial Intelligence or Electronics and Electrical Engineering.
· Strong interest in Cyber Security and Artificial Intelligence