| Title | Matrix profile for DDoS attacks detection |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Alotaibi, Faisal, Lisitsa, Alexei |
| Conference Name | 2021 16th Conference on Computer Science and Intelligence Systems (FedCSIS) |
| Keywords | Computer crime, computer networks, Computer science, DDoS attack detection, denial-of-service attack, Human Behavior, Metrics, Network security, pubcrawl, resilience, Resiliency, Time series analysis |
| Abstract | Several previous studies have focused on Distributed Denial of Service (DDoS) attacks, which are a crucial problem in computer network security. In this paper we explore the applicability of a a time series method known as a matrix profile to the anomaly based DDoS attacks detection. The study thus examined how the matrix profile method performed in diverse situations related to DDoS attacks, as well as identifying those features that are most applicable in various scenarios. Based on reported empirical evaluation the matrix profile method is shown to be efficient against most of the considered types of DDoS attacks. |
| DOI | 10.15439/2021F114 |
| Citation Key | alotaibi_matrix_2021 |
Matrix profile for DDoS attacks detection