Classifiers for Behavioral Patterns Identification Induced from Huge Temporal Data
| dc.contributor.author | Bazan, Jan. G. | |
| dc.contributor.author | Szpyrka, Marcin | |
| dc.contributor.author | Szczur, Adam | |
| dc.contributor.author | Dydo, Łukasz | |
| dc.contributor.author | Wojtowicz, Hubert | |
| dc.date.accessioned | 2014-11-14T18:11:55Z | |
| dc.date.available | 2014-11-14T18:11:55Z | |
| dc.date.issued | 2014 | |
| dc.description | Praca opublikowana w: Bazan, J., G., Szpyrka, M., Szczur, A., Dydo, L., Wojtowicz, H.: Classifiers for Behavioral Patterns Identification Induced from Huge Temporal Data, In Proceedings of the Workshop on Concurrency, Specification and Programming (CS&P 2014), Chemnitz, Germany, 2014, September 29-October 1, volume 245 of Informatik-Bericht, pages 22-33, Humboldt University, 2014. | pl_PL.UTF-8 |
| dc.description.abstract | A new method of constructing classifiers from huge volume of temporal data is proposed in the paper. The novelty of introduced method lies in a multi-stage approach to constructing hierarchical classifiers that combines process mining, feature extraction based on temporal patterns and constructing classifiers based on a decision tree. Such an approach seems to be practical when dealing with huge volume of temporal data. As a proof of concept a system has been constructed for packet-based network traffic anomaly detection, where anomalies are represented by spatio-temporal complex concepts and called by behavioral patterns. Hierarchical classifiers constructed with the new approach turned out to be better than ”flat” classifiers based directly on captured network traffic data. | pl_PL.UTF-8 |
| dc.description.sponsorship | This work was partially supported by the Polish National Science Centre grant DEC-2013/09/B/ ST6/01568 and by the Centre for Innovation and Transfer of Natural Sciences and Engineering Knowledge of University of Rzeszów, Poland. | pl_PL.UTF-8 |
| dc.identifier.uri | http://repozytorium.ur.edu.pl/handle/item/672 | |
| dc.language.iso | eng | pl_PL.UTF-8 |
| dc.publisher | Humboldt University | pl_PL.UTF-8 |
| dc.subject | classifiers | pl_PL.UTF-8 |
| dc.subject | huge temporal data | pl_PL.UTF-8 |
| dc.subject | temporal patterns | pl_PL.UTF-8 |
| dc.subject | state graphs | pl_PL.UTF-8 |
| dc.subject | behavioral patterns | pl_PL.UTF-8 |
| dc.subject | LTL temporal logic | pl_PL.UTF-8 |
| dc.title | Classifiers for Behavioral Patterns Identification Induced from Huge Temporal Data | pl_PL.UTF-8 |
| dc.type | conferenceObject | pl_PL.UTF-8 |