Laurens D'hooge

According to our database, Laurens D'hooge authored at least 15 papers between 2019 and 2023.

Collaborative distances:

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

2023

A Novel Multi-Stage Approach for Hierarchical Intrusion Detection.

Miel Verkerken, Laurens D'hooge, Didik Sudyana, Ying-Dar Lin, Tim Wauters, Bruno Volckaert, Filip De Turck

IEEE Trans. Netw. Serv. Manag., September, 2023

Characterizing the Impact of Data-Damaged Models on Generalization Strength in Intrusion Detection.

Laurens D'hooge, Miel Verkerken, Tim Wauters, Filip De Turck, Bruno Volckaert

J. Cybersecur. Priv., April, 2023

Task Assignment and Capacity Allocation for ML-Based Intrusion Detection as a Service in a Multi-Tier Architecture.

Yuan-Cheng Lai, Didik Sudyana, Ying-Dar Lin, Miel Verkerken, Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

IEEE Trans. Netw. Serv. Manag., March, 2023

Investigating Generalized Performance of Data-Constrained Supervised Machine Learning Models on Novel, Related Samples in Intrusion Detection.

Laurens D'hooge, Miel Verkerken, Tim Wauters, Filip De Turck, Bruno Volckaert

Sensors, February, 2023

Castles Built on Sand: Observations from Classifying Academic Cybersecurity Datasets with Minimalist Methods.

Laurens D'hooge, Miel Verkerken, Tim Wauters, Filip De Turck, Bruno Volckaert

Proceedings of the 8th International Conference on Internet of Things, 2023

Performance Impact of Queue Sorting in Container-Based Application Scheduling.

José Santos, Miel Verkerken, Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

Proceedings of the 19th International Conference on Network and Service Management, 2023

2022

Towards Model Generalization for Intrusion Detection: Unsupervised Machine Learning Techniques.

Miel Verkerken, Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

J. Netw. Syst. Manag., 2022

Discovering Non-Metadata Contaminant Features in Intrusion Detection Datasets.

Laurens D'hooge, Miel Verkerken, Tim Wauters, Bruno Volckaert, Filip De Turck

Proceedings of the 19th Annual International Conference on Privacy, Security & Trust, 2022

Establishing the Contaminating Effect of Metadata Feature Inclusion in Machine-Learned Network Intrusion Detection Models.

Laurens D'hooge, Miel Verkerken, Bruno Volckaert, Tim Wauters, Filip De Turck

Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2022

2021

Hierarchical feature block ranking for data-efficient intrusion detection modeling.

Laurens D'hooge, Miel Verkerken, Tim Wauters, Bruno Volckaert, Filip De Turck

Comput. Networks, 2021

Machine learning based intrusion detection as a service: task assignment and capacity allocation in a multi-tier architecture.

Yuan-Cheng Lai, Didik Sudyana, Ying-Dar Lin, Miel Verkerken, Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

Proceedings of the UCC '21: 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing, Leicester, United Kingdom, December 6 - 9, 2021, 2021

2020

Inter-dataset generalization strength of supervised machine learning methods for intrusion detection.

Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

J. Inf. Secur. Appl., 2020

Unsupervised Machine Learning Techniques for Network Intrusion Detection on Modern Data.

Miel Verkerken, Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

Proceedings of the 4th Cyber Security in Networking Conference, 2020

2019

Classification Hardness for Supervised Learners on 20 Years of Intrusion Detection Data.

Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

IEEE Access, 2019

In-depth Comparative Evaluation of Supervised Machine Learning Approaches for Detection of Cybersecurity Threats.

Laurens D'hooge, Tim Wauters, Bruno Volckaert, Filip De Turck

Proceedings of the 4th International Conference on Internet of Things, 2019