Abstract
Performing both security vulnerability assessment and configuration processes are heavily reliant on expert knowledge. This requirement often results in many systems being left insecure due to a lack of analysis expertise and access to specialist resources. It has long been known that a system's event log provides historical information depicting potential security threats, as well as recording configuration activities. In this paper, a novel technique is developed that can process security event logs on a computer that has been assessed and configured by a security professional, and autonomously establish causality amongst event log entries to learn performed configuration tasks. This extracted knowledge can then be exploited by non-professionals to plan steps that can improve the security of a previously unseen system
Original language | English |
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Title of host publication | Proceedings of the 9th International Conference on Knowledge Capture (K-CAP), (Austin, TX: 4-6 December 2017) |
Publisher | Association for Computing Machinery (ACM) |
Number of pages | 4 |
ISBN (Electronic) | 9781450355537 |
DOIs | |
Publication status | Published - 4 Dec 2017 |
Event | 9th International Conference on Knowledge Capture - Hilton Garden Inn Convention Center, Austin, United States Duration: 4 Dec 2017 → 6 Dec 2017 Conference number: 9 https://k-cap2017.org/ (Link to Conference Website) |
Conference
Conference | 9th International Conference on Knowledge Capture |
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Abbreviated title | K-CAP 2017 |
Country/Territory | United States |
City | Austin |
Period | 4/12/17 → 6/12/17 |
Internet address |
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