Cybersecurity Research Engineer
I am a 4th year PhD student and a Cyber Security Research engineer. My research interests revolve around the security of Industrial Control Systems and Internet of Things devices. More specifically, I research how machine learning methods can be used to defend such systems.
Few of the awards I have won over the past couple of years include:
- A member of a team awarded 1st place in an open-source intelligence competition, 2019.
- Best paper award at the second EAI International Conference on Cloud, Networking for IoT Systems in Italy, 2017.
- Best research poster, Cardiff University, 2017.
Eirini Anthi is a lecturer at the School of Computer Science & Informatics, Cardiff University. Her research interests revolve around the security of the Internet of Things (IoT), SCADA, and Industrial Control Systems. More particularly, her research examines the security issues that come along with these devices/systems and focuses on developing intelligent and more robust cyber-attack detection mechanisms for such networks using machine learning and adversarial machine learning techniques. As part of her doctorate, she developed state-of-the-art tools to detect and defend against network-based cyber attacks in such infrastructures.
Over the past 3 years apart from giving a range of guest lectures, assisting with labs, and creating CTF based teaching events, I have also supervised more than 20 state-of-art research based final year projects in cyber security for both postrgaduate and undergraduate students. Few of the projects I supervised included:
- Investigating adversarial machine learning against malware detection systems
- Investigating Malware propagation via IoT devices to internal networks
- Vulnerability assessment and risk modeling of attacks in IT systems
- Detecting network based attacks in Industrial Control Systems
- Evaluating the robustness of a lattice-based cryptosystem
- Investigating the Security and Privacy of a Real-World Internet of Things Environment (During the project the student Identified and reported to the company a vulnerability against the IoT device)
- Investigation and analysis of security issues in smartphone applications
- Intelligent Attack Detection for IoT Networks (Led to publication)
- Investigating Radio Frequency vulnerabilities in the Internet of Things using HackRF (Aim to produce a publication)
- Cryptanalysis of a Wireless Security System
- Simulating the Effects of Releasing Malware into the Internet of Things
- Security Issues, Privacy, and Challenges in the Internet of Things: Vulnerabilities, Threats and Attacks.
- Hardening Machine Learning Denial of Service (DoS) Defences Against Adversarial Attacks in IoT Smart Home Networks. Anthi, E., Williams, L., Javed, A. and Burnap, P., 2021. Computers & Security, p.102352.
- Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems.
Anthi, E., Williams, L., Rhode, M., Burnap, P. and Wedgbury, A., 2021. Journal of Information Security and Applications, 58, p.102717.
- A three-tiered intrusion detection system for industrial control systems. Anthi, E., Williams, L., Burnap, P. and Jones, K., 2021. Journal of Cybersecurity, 7(1), p.tyab006.
- Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments–cyber risk in the colonisation of Mars. Radanliev, P., De Roure, D., Page, K., Van Kleek, M., Santos, O., Burnap, P., Anthi, E. and Maple, C., 2021. Safety in Extreme Environments, pp.1-12.
- Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge. Radanliev, P., De Roure, D., Van Kleek, M., Ani, U., Burnap, P., Anthi, E., Nurse, J.R., Santos, O. and Montalvo, R.M., 2020. Environment Systems and Decisions, pp.1-12.
- Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge. Radanliev, P., De Roure, D., Walton, R., Van Kleek, M., Montalvo, R.M., Santos, O., Burnap, P. and Anthi, E., 2020. SN Applied Sciences, 2(11), pp.1-8.
- A supervised intrusion detection system for smart home IoT devices
Eirini Anthi, Lowri Williams, Slowinska Malgorzata, Georgios Theodorakopoulos, Peter Burnap,
IEEE Internet of Things 2019-10-31 Volume:6 Number:5 Page Range: 9042-9053
- Cyber risk from IoT technologies in the supply chain–discussion on supply chains decision support system for the digital economy. Radanliev, P., De Roure, D.C., Nurse, J.R., Burnap, P., Anthi, E., Ani, U., Maddox, L., Santos, O. and Montalvo, R.M., 2019.
- Cyber risk management for the Internet of Things. Radanliev, P., De Roure, D.C., Nurse, J.R., Burnap, P., Anthi, E., Uchenna, A., Santos, O. and Montalvo, R.M., 2019. Univ. Oxford, pp.1-27.
- EclipseIoT: A secure and adaptive hub for the Internet of Things
Computers and Security
Eirini Anthi, Shazaib Ahmad, Omer Rana, Pete Burnap, Georgios Theodorakopoulos,
2018-09-01 Volume:78Page Range:477-490
- Pulse: an adaptive intrusion detection for the internet of things. Anthi, E., Williams, L. and Burnap, P., 2018.
- Secure data sharing and analysis in cloud-based energy management systems
Eirini Anthi, Amir Javed, Omer F. Rana, Georgios Theodorakopoulos, Antonella Longo, Marco Zappatore, Massimo Villari, Omer Rana, Dario Bruneo, Rajiv Ranjan, Maria Fazin, Philippe Massonet,
2017-10-27 Volume:189Page Range:228-242
- Sensitive data in Smartphone Applications: Where does it go? Can it be intercepted?
Eirini Anthi, Georgios Theodorakopoulos, 2017
- Internet of Things Security
- Industrial Control Systems Security
- Malware Analysis
- Network Security
- Machine Learning