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@inproceedings{26086, author = {Husák, Martin and Kašpar, Jaroslav and BouandHarb, Elias and Čeleda, Pavel}, address = {Reggio Calabria}, booktitle = {Proceedings of the 12th International Conference on Availability, Reliability and Security}, keywords = {data mining;cyber security;sequential pattern mining;sequential rule mining;alert correlation;attack prediction}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Reggio Calabria}, isbn = {978-1-4503-5257-4}, pages = {"22:1"-"22:10"}, publisher = {ACM}, title = {On the Sequential Pattern and Rule Mining in the Analysis of Cyber Security Alerts}, url = {https://dl.acm.org/citation.cfm?doid=3098954.3098981}, year = {2017} }
TY - JOUR ID - 26086 AU - Husák, Martin - Kašpar, Jaroslav - Bou-Harb, Elias - Čeleda, Pavel PY - 2017 TI - On the Sequential Pattern and Rule Mining in the Analysis of Cyber Security Alerts PB - ACM CY - Reggio Calabria SN - 9781450352574 KW - data mining;cyber security;sequential pattern mining;sequential rule mining;alert correlation;attack prediction UR - https://dl.acm.org/citation.cfm?doid=3098954.3098981 N2 - Data mining is well-known for its ability to extract concealed and indistinct patterns in the data, which is a common task in the field of cyber security. However, data mining is not always used to its full potential among cyber security community. In this paper, we discuss usability of sequential pattern and rule mining, a subset of data mining methods, in an analysis of cyber security alerts. First, we survey the use case of data mining, namely alert correlation and attack prediction. Subsequently, we evaluate sequential pattern and rule mining methods to find the one that is both fast and provides valuable results while dealing with the peculiarities of security alerts. An experiment was performed using the dataset of real alerts from an alert sharing platform. Finally, we present lessons learned from the experiment and a comparison of the selected methods based on their performance and soundness of the results. ER -
HUSÁK, Martin, Jaroslav KAŠPAR, Elias BOU-HARB and Pavel ČELEDA. On the Sequential Pattern and Rule Mining in the Analysis of Cyber Security Alerts. Online. In \textit{Proceedings of the 12th International Conference on Availability, Reliability and Security}. Reggio Calabria: ACM, 2017, p.~''22:1''-''22:10'', 10 pp. ISBN~978-1-4503-5257-4.
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