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bib
--- Timezone: CEST
Creation date: 2024-05-17
Creation time: 04-45-49
--- Number of references
1
inproceedings
2023_sloun_accessibility
Poster: Vulcan - Repurposing Accessibility Features for Behavior-based Intrusion Detection Dataset Generation
2023
11
27
3543-3545
The generation of datasets is one of the most promising approaches to collecting the necessary behavior data to train machine learning models for host-based intrusion detection. While various dataset generation methods have been proposed, they are often limited and either only generate network traffic or are restricted to a narrow subset of applications. We present Vulcan, a preliminary framework that uses accessibility features to generate datasets by simulating user interactions for an extendable set of applications. It uses behavior profiles that define realistic user behavior and facilitate dataset updates upon changes in software versions, thus reducing the effort required to keep a dataset relevant. Preliminary results show that using accessibility features presents a promising approach to improving the quality of datasets in the HIDS domain.
Intrusion Detection, Dataset Generation, Accessibility Features
https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-sloun-vulcan-accessibility.pdf
ACM
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS '23), November 26-30, 2023, Copenhagen, Denmark
Copenhagen, Denmark
November 26-30, 2023
979-8-4007-0050-7/23/11
10.1145/3576915.3624404
1
Christianvan Sloun
KlausWehrle