Informační systém Repo
HUSÁK, Martin, Jaroslav KAŠPAR, Elias BOU-HARB a Pavel ČELEDA. On the Sequential Pattern and Rule Mining in the Analysis of Cyber Security Alerts. In Proceedings of the 12th International Conference on Availability, Reliability and Security. Reggio Calabria: ACM, 2017. s. "22:1-22:10", 10 s. ISBN 978-1-4503-5257-4.
Další formáty:   BibTeX LaTeX RIS
Základní údaje
Originální název On the Sequential Pattern and Rule Mining in the Analysis of Cyber Security Alerts
Autoři HUSÁK, Martin, Jaroslav KAŠPAR, Elias BOU-HARB a Pavel ČELEDA.
Vydání Reggio Calabria, Proceedings of the 12th International Conference on Availability, Reliability and Security, od s. "22:1-22:10", 10 s. 2017.
Nakladatel ACM
Další údaje
Originální jazyk angličtina
Typ výsledku Článek ve sborníku
Obor Informatika
Stát vydavatele Spojené státy americké
Utajení není předmětem státního či obchodního tajemství
Forma vydání elektronická verze "online"
Organizace Ústav výpočetní techniky - Masarykova univerzita
ISBN 978-1-4503-5257-4
Klíčová slova anglicky data mining;cyber security;sequential pattern mining;sequential rule mining;alert correlation;attack prediction
Návaznosti VI20162019029, projekt VaV.
Změnil Změnil: RNDr. Daniel Jakubík, učo 139797. Změněno: 18. 8. 2017 00:55.
Anotace
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.
Zobrazeno: 22. 11. 2017 12:18