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.
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 Open Access version: https://hdl.handle.net/10289/12888
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