dc.contributor.author | Paulauskas, Nerijus | |
dc.contributor.author | Baškys, Algirdas | |
dc.date.accessioned | 2023-09-18T20:15:05Z | |
dc.date.available | 2023-09-18T20:15:05Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 2079-9292 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/148203 | |
dc.description.abstract | Misuse activity in computer networks constantly creates new challenges and difficulties to ensure data confidentiality, integrity, and availability. The capability to identify and quickly stop the attacks is essential, as the undetected and successful attack may cause losses of critical resources. The anomaly-based intrusion detection system (IDS) is a valuable security tool that is capable of detecting new, previously unseen attacks. Anomaly-based IDS sends an alarm when it detects an event that deviates from the behavior characterized as normal. This paper analyses the use of the histogram-based outlier score (HBOS) to detect anomalies in the computer network. Experimental results of different histogram creation methods and the influence of the number of bins on the performance of anomaly detection are presented. Experiments were conducted using an NSL-KDD dataset. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-8 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | DOAJ | |
dc.relation.isreferencedby | INSPEC | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.source.uri | https://doi.org/10.3390/electronics8111251 | |
dc.title | Application of histogram-based outlier scores to detect computer network anomalies | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.license | Creative Commons – Attribution – 4.0 International | |
dcterms.references | 15 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas Valstybinis mokslinių tyrimų institutas Fizinių ir technologijos mokslų centras | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.researchfield | N 002 - Fizika / Physics | |
dc.subject.vgtuprioritizedfields | IK0101 - Informacijos ir informacinių technologijų sauga / Information and Information Technologies Security | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | anomaly detection | |
dc.subject.en | intrusion detection | |
dc.subject.en | network security | |
dc.subject.en | histogram-based outlier score (HBOS) | |
dcterms.sourcetitle | Electronics | |
dc.description.issue | iss. 11 | |
dc.description.volume | vol. 8 | |
dc.publisher.name | MDPI | |
dc.publisher.city | Basel | |
dc.identifier.doi | 10.3390/electronics8111251 | |
dc.identifier.elaba | 43070269 | |