Machine Learning in Cyber-Security - Problems, Challenges and Data Sets
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Abstract (arXiv)
We present cyber-security problems of high importance. We show that in order to solve these cyber-security problems, one must cope with certain machine learning challenges. We provide novel data sets representing the problems in order to enable the academic community to investigate the problems and suggest methods to cope with the challenges. We also present a method to generate labels via pivoting, providing a solution to common problems of lack of labels in cyber-security.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Dec 2018.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 1; 2024: 0; 2025: 1.
5 papers.
- 2021Follow Your Nose -- Which Code Smells are Worth Chasing?cited by 4
- 2021Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networkscited by 3
- 2021ComSum: Commit Messages Summarization and Meaning Preservationcited by 3
- 2025A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network Securitycited by 1
- 2023Fast likelihood-based change point detectioncited by 0
- 2025A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network Security14 Jan 2025
- 2023Fast likelihood-based change point detection21 Jan 2023
- 2021ComSum: Commit Messages Summarization and Meaning Preservation23 Aug 2021
- 2021Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks19 Apr 2021
- 2021Follow Your Nose -- Which Code Smells are Worth Chasing?2 Mar 2021