dc.contributor.author | Auškalnis, Juozas | |
dc.contributor.author | Paulauskas, Nerijus | |
dc.contributor.author | Baškys, Algirdas | |
dc.date.accessioned | 2023-09-18T17:16:43Z | |
dc.date.available | 2023-09-18T17:16:43Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 1392-1215 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/121216 | |
dc.description.abstract | Gap between the new attack appearance and signature creation for this attack may be critical. During this time, many computer systems may be affected and valuable resources may be lost. Even after signature creation, many computer systems still stay vulnerable because of bad security practice, i.e. patches and updates are not installed as needed. Therefore, anomaly intrusion detection system (IDS) that is capable to detect new unknown attacks is valuable security tool. This paper analyses the use of Local Outlier Factor (LOF) to detect anomalies in the computer network. The application of the LOF algorithm for the detection of anomalies when only normal network data are used for the model training has been demonstrated. Experimental results of different threshold values influence on the anomaly detection accuracy using NSLKDD dataset is presented. | eng |
dc.format | PDF | |
dc.format.extent | p. 96-99 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | VINITI | |
dc.relation.isreferencedby | INSPEC | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.source.uri | http://dx.doi.org/10.5755/j01.eie.24.3.20972 | |
dc.subject | IK02 - Išmaniosios komunikacijų technologijos / Smart communication technologies | |
dc.title | Application of local outlier factor algorithm to detect anomalies in computer network | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 9 | |
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.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | Intrusion detection | |
dc.subject.en | Anomaly detection | |
dc.subject.en | Local outlier factor | |
dcterms.sourcetitle | Elektronika ir elektrotechnika = Electronics and electrical engineering | |
dc.description.issue | iss. 3 | |
dc.description.volume | vol. 24 | |
dc.publisher.name | Technologija | |
dc.publisher.city | Kaunas | |
dc.identifier.doi | 000436583500015 | |
dc.identifier.doi | 2-s2.0-85049811483 | |
dc.identifier.doi | 10.5755/j01.eie.24.3.20972 | |
dc.identifier.elaba | 29753891 | |