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Cyber Security, Artificial Intelligence, Machine Learning and Blockchain Technology: Mitigating Cyber Attacks and Detecting Malicious Activities in Network Traffic


   Faculty of Engineering and Informatics


About the Project

Cyber attacks have become more widespread and several attacks have made headline news over the past decade, targeting industrial companies and governmental organisations. 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, cybersecurity 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). Besides, blockchain technology provides high standards of data transparency and integrity.

This project aims to tackle Trust, Identity, Privacy and Security (TIPS) issues in large-scale networks, Internet of Things, Wireless Communications and Smart Cities. The proposed research aims at developing a practically deployable cyber security solution to one or more of the cyber threats. Multi-Stage Attacks (MSAs), Advanced Persistent Threats (APTs), ransomware / malware, social engineering, Distributed Denial of Service (DDoS) attacks, wireless injection attacks, botnets or other malicious activities will be investigated. The developed methods aim to analyse the cybersecurity vulnerabilities and will be based on advanced Artificial Intelligence (AI) technologies. Network security monitor tools will be used to analyse the network traffic and a novel Intrusion Detection System (IDS) will be developed using cutting-edge Machine / Deep Learning algorithms. Moreover, the blockchain technology and smart contracts can be utilised to strengthen cybersecurity and keep information safe.

The project offers the candidate new opportunities to gain invaluable experience in the relevant areas. The successful candidate will have the opportunity to work within a dynamic, effective and multi-disciplinary team.

Person Specification

  • 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, Artificial Intelligence, Machine Learning and Blockchain Technology.
  • Programming experience (any language, e.g. Java, C, R, Python, Matlab)
  • Good analytical skills - knowledge of foundations of computer science, ability to think independently
  • Strong oral and written communication skills, in both plain English and academic languages, for publication in relevant journals and presentation at conferences

Funding Notes

This is a self-funded PhD project; applicants will be expected to pay their own fees or have a suitable source of third-party funding. UK students may be able to apply for a Doctoral Loan from Student Finance for financial support.

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