Publication Date:
2022
Citation:
Pattern Matching Algorithm in Event Graphs / V. Bellandi, P. Ceravolo, S. Maghool, M. Pindaro, S. Siccardi - In: International Symposium on Dependable, Autonomic and Secure Computing (DASC)[s.l] : Institute of Electrical and Electronics Engineers (IEEE), 2022. - ISBN 978-1-6654-6298-3. - pp. 1-7 (( Intervento presentato al 20. convegno International Conference on Dependable, Autonomic and Secure Computing, 20th IEEE International Conference on Pervasive Intelligence and Computing, 7th IEEE International Conference on Cloud and Big Data Computing, 2022 IEEE International Conference on Cyber Science and Technology Congress : 12 - 15 September tenutosi a Falerna (CZ Italy) nel 2022 [10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927860].
abstract:
Event-graphs are used for modelling and analyzing discrete data that usually represent activities and so on. In this work we take into analysis this kind of graphs and the problem of identifying correlations among events. We propose a methodology to first identify events that are significantly correlated and then to event patterns. Both are often related to individual entities and their behaviour, so that their specificity can be spotted in a complex event network. In the last part of the paper we describe our experimental results.
IRIS type:
03 - Contributo in volume
Keywords:
Correlations; Event graphs; Pattern matching;
List of contributors:
V. Bellandi, P. Ceravolo, S. Maghool, M. Pindaro, S. Siccardi
Link to information sheet:
Book title:
International Symposium on Dependable, Autonomic and Secure Computing (DASC)