Duc C. Le

According to our database, Duc C. Le authored at least 17 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Anomaly Detection for Insider Threats Using Unsupervised Ensembles.

Duc C. Le, Nur Zincir-Heywood

IEEE Trans. Netw. Serv. Manag., 2021

Exploring anomalous behaviour detection and classification for insider threat identification.

Duc C. Le, Nur Zincir-Heywood

Int. J. Netw. Manag., 2021

Training regime influences to semi-supervised learning for insider threat detection.

Duc C. Le, Nur Zincir-Heywood, Malcolm I. Heywood

Proceedings of the IEEE Security and Privacy Workshops, 2021

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

A Frontier: Dependable, Reliable and Secure Machine Learning for Network/System Management.

Duc C. Le, Nur Zincir-Heywood

J. Netw. Syst. Manag., 2020

Exploring Adversarial Properties of Insider Threat Detection.

Duc C. Le, Nur Zincir-Heywood

Proceedings of the 8th IEEE Conference on Communications and Network Security, 2020

2019

Big Data in Network Anomaly Detection.

Duc C. Le, Nur Zincir-Heywood

Proceedings of the Encyclopedia of Big Data Technologies., 2019

Unsupervised Monitoring of Networkand Service Behaviour Using SelfOrganizing Maps.

Duc C. Le, Nur Zincir-Heywood, Malcolm I. Heywood

J. Cyber Secur. Mobil., 2019

Dynamic Insider Threat Detection Based on Adaptable Genetic Programming.

Duc C. Le, Nur Zincir-Heywood, Malcolm I. Heywood

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Machine learning based Insider Threat Modelling and Detection.

Duc C. Le, Nur Zincir-Heywood

Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, 2019

Benchmarking genetic programming in dynamic insider threat detection.

Duc C. Le, Malcolm I. Heywood, Nur Zincir-Heywood

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Learning From Evolving Network Data for Dependable Botnet Detection.

Duc C. Le, Nur Zincir-Heywood

Proceedings of the 15th International Conference on Network and Service Management, 2019

Exploring Feature Normalization and Temporal Information for Machine Learning Based Insider Threat Detection.

Pedro Ferreira, Duc C. Le, Nur Zincir-Heywood

Proceedings of the 15th International Conference on Network and Service Management, 2019

2018

Evaluating Insider Threat Detection Workflow Using Supervised and Unsupervised Learning.

Duc C. Le, Nur Zincir-Heywood

Proceedings of the 2018 IEEE Security and Privacy Workshops, 2018

Benchmarking evolutionary computation approaches to insider threat detection.

Duc C. Le, Sara Khanchi, Nur Zincir-Heywood, Malcolm I. Heywood

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

2016

Data analytics on network traffic flows for botnet behaviour detection.

Duc C. Le, Nur Zincir-Heywood, Malcolm I. Heywood

Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

2015

On the Effectiveness of Different Botnet Detection Approaches.

Fariba Haddadi, Duc Le Cong, Laura Porter, Nur Zincir-Heywood

Proceedings of the Information Security Practice and Experience, 2015