Dr Abigail Koay
Qualifications: BCompSci (UMP), PhD in Engineering (VUW)
Phone: +6 07 838 4926
Dr. Abigail Koay is a Research Fellow at the Department of Computer Science, University of Waikato. She received her Bachelors of Computer Science from University Malaysia Pahang, Malaysia and her Ph.D. in Engineering (Network Security) from Victoria University of Wellington, New Zealand. Her Ph.D. research focuses on detecting Distributed Denial of Service (DDoS) attacks on large-scale networks. She studies the use of entropy-based features and the applicability of machine learning algorithms in detecting various intensity DDoS attacks. She also applies software-defined networking technology to address some of the network architecture issues in detecting DDOS attacks from multiple locations in the network. Abigail’s current research interest are Network Security, Traffic Anomaly Detection, Anomaly Detection in IoT Devices, Software-Defined Networking and Applied Machine Learning.
I am currently looking for a student to work on "Project #23 - Traffic Classification and Anomaly Detection using Poseidon" under the University of Waikato Summer Research Scholarships over summer 2019/2020. If you are interested, please find more details of the project and application eligibility at
Application deadline: 15th September 2019.
Sacha Raman (Honours Project - Creating Hardware-based CHallenges for Cyber Security Competition) - with Dr. Vimal Kumar
Rhys Compton (Honours Project – Machine Learning for Optimization of the JVM) – with Prof Eibe Frank and Dr Panos Patros;
Kriti Narsapur (PgDip Research – Detecting Compromised Insulin Pumps in Closed-Loop Artificial Pancreas System) – with Dr. Mike Mayo
Mitchell Grout (Masters Research – Applicability of Neuroevolution Techniques in Detecting Distributed Denial of Service Attacks) – with Dr Richard Nelson
Podolskiy, V., Mayo, M., Koay, A., Gerndt, M., & Patros, P. (2019). Maintaining SLOs of cloud-native applications via self-adaptive resource sharing. In Proc 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2019) (pp. 72-81). Umeå, Sweden: IEEE. doi:10.1109/SASO.2019.00018
Koay, A., Welch, I., & Seah, W. K. G. (2019). Effectiveness of entropy-based features in high-and low-intensity DDoS attacks detection. In N. Attrapadung, & T. Yagi (Eds.), Proc 14th International Workshop on Security (IWSEC 2019), Advances in Information and Computer Security, LNCS 11689 (pp. 207-217). Tokyo, Japan: Springer. doi:10.1007/978-3-030-26834-3_12
Koay, A., Chen, A., Welch, I., & Seah, W. K. G. (2018). A new multi classifier system using entropy-based features in DDoS attack detection. In Proc 2018 International Conference on Information Networking (ICOIN) (pp. 162-167). Boston, USA: IEEE. doi:10.1109/icoin.2018.8343104
Find more research publications by Abigail Koay