dc.contributor.author | Bodström, Tero | |
dc.contributor.author | Hämäläinen, Timo | |
dc.contributor.editor | Galinina, Olga | |
dc.contributor.editor | Andreev, Sergey | |
dc.contributor.editor | Balandin, Sergey | |
dc.contributor.editor | Koucheryavy, Yevgeni | |
dc.date.accessioned | 2018-10-26T09:12:31Z | |
dc.date.available | 2019-09-30T21:35:34Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Bodström, T., & Hämäläinen, T. (2018). State of the art literature review on Network Anomaly Detection. In O. Galinina, S. Andreev, S. Balandin, & Y. Koucheryavy (Eds.), <i>NEW2AN : Proceedings of the 18th International Conference on Next Generation Wired/Wireless Advanced Networks and Systems</i> (pp. 89-101). Springer. Lecture Notes in Computer Science, 11118. <a href="https://doi.org/10.1007/978-3-030-01168-0_9" target="_blank">https://doi.org/10.1007/978-3-030-01168-0_9</a> | |
dc.identifier.other | CONVID_28281623 | |
dc.identifier.other | TUTKAID_78945 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/59962 | |
dc.description.abstract | As network attacks are evolving along with extreme growth
in the amount of data that is present in networks, there is a significant
need for faster and more effective anomaly detection methods. Even
though current systems perform well when identifying known attacks,
previously unknown attacks are still difficult to identify under occurrence.
To emphasize, attacks that might have more than one ongoing
attack vectors in one network at the same time, or also known as APT
(Advanced Persistent Threat) attack, may be hardly notable since it
masquerades itself as legitimate traffic. Furthermore, with the help of
hiding functionality, this type of attack can even hide in a network for
years. Additionally, the expected number of connected devices as well
as the fast-paced development caused by the Internet of Things, raises
huge risks in cyber security that must be dealt with accordingly. When
considering all above-mentioned reasons, there is no doubt that there
is plenty of room for more advanced methods in network anomaly detection
hence more advanced statistical methods and machine learning
based techniques have been proposed recently in detecting anomalies. | fi |
dc.format.extent | 705 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Springer | |
dc.relation.ispartof | NEW2AN : Proceedings of the 18th International Conference on Next Generation Wired/Wireless Advanced Networks and Systems | |
dc.relation.ispartofseries | Lecture Notes in Computer Science | |
dc.rights | In Copyright | |
dc.subject.other | network anomaly detection | |
dc.title | State of the art literature review on Network Anomaly Detection | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-201810044358 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2018-10-04T15:15:11Z | |
dc.relation.isbn | 978-3-030-01167-3 | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 89-101 | |
dc.relation.issn | 0302-9743 | |
dc.relation.numberinseries | 11118 | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © Springer Nature Switzerland AG 2018 | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | International Conference on Next Generation Wired/Wireless Advanced Networks and Systems | |
dc.subject.yso | tietoturva | |
dc.subject.yso | verkkohyökkäykset | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p5479 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p27466 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1007/978-3-030-01168-0_9 | |
dc.type.okm | A4 | |