On the Effectiveness of Different Botnet Detection Approaches. - Fariba Haddadi; Duc Le Cong; Laura Porter; Nur Zincir-Heywood (ISPEC, 2015)

Data analytics on network traffic flows for botnet behaviour detection. - Duc C. Le; Nur Zincir-Heywood; Malcolm I. Heywood (SSCI, 2016)

Benchmarking evolutionary computation approaches to insider threat detection. - Duc C. Le; Sara Khanchi; Nur Zincir-Heywood; Malcolm I. Heywood (GECCO, 2018)

Evaluating Insider Threat Detection Workflow Using Supervised and Unsupervised Learning. - Duc C. Le; Nur Zincir-Heywood (IEEE Symposium on Security and Privacy Workshops, 2018)

Exploring Feature Normalization and Temporal Information for Machine Learning Based Insider Threat Detection. - Pedro Ferreira; Duc C. Le; Nur Zincir-Heywood (CNSM, 2019)

Learning From Evolving Network Data for Dependable Botnet Detection. - Duc C. Le; Nur Zincir-Heywood (CNSM, 2019)

Benchmarking genetic programming in dynamic insider threat detection. - Duc C. Le; Malcolm I. Heywood; Nur Zincir-Heywood (GECCO (Companion), 2019)

Machine learning based Insider Threat Modelling and Detection. - Duc C. Le; Nur Zincir-Heywood (IM, 2019)

Dynamic Insider Threat Detection Based on Adaptable Genetic Programming. - Duc C. Le; Nur Zincir-Heywood; Malcolm I. Heywood (SSCI, 2019)

Unsupervised Monitoring of Networkand Service Behaviour Using SelfOrganizing Maps. - Duc C. Le; Nur Zincir-Heywood; Malcolm I. Heywood (J. Cyber Secur. Mobil., 2019)

Big Data in Network Anomaly Detection. - Duc C. Le; Nur Zincir-Heywood (Encyclopedia of Big Data Technologies, 2019)

Exploring Adversarial Properties of Insider Threat Detection. - Duc C. Le; Nur Zincir-Heywood (CNS, 2020)

A Frontier: Dependable, Reliable and Secure Machine Learning for Network/System Management. - Duc C. Le; Nur Zincir-Heywood (J. Netw. Syst. Manag., 2020)

Analyzing Data Granularity Levels for Insider Threat Detection Using Machine Learning. - Duc C. Le; Nur Zincir-Heywood; Malcolm I. Heywood (IEEE Trans. Netw. Serv. Manag., 2020)

Training regime influences to semi-supervised learning for insider threat detection. - Duc C. Le; Nur Zincir-Heywood; Malcolm I. Heywood (SP (Workshops), 2021)

Exploring anomalous behaviour detection and classification for insider threat identification. - Duc C. Le; Nur Zincir-Heywood (Int. J. Netw. Manag., 2021)

Anomaly Detection for Insider Threats Using Unsupervised Ensembles. - Duc C. Le; Nur Zincir-Heywood (IEEE Trans. Netw. Serv. Manag., 2021)