An Anomaly Detection System Proposal to Ensure Information Security for File Integrations

dc.contributor.authorUzum, Ibrahim
dc.contributor.authorCan, Ozgu
dc.date.accessioned2021-05-03T20:41:39Z
dc.date.available2021-05-03T20:41:39Z
dc.date.issued2018
dc.departmentEge Üniversitesien_US
dc.description26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEYen_US
dc.description.abstractAnomaly detection has an important place in the field of information security with the reason for providing defense against new threats. Additionally, anomaly detection can help organizations to make plan for the unexpected situations. For this reason, it is important to take into account that abnormalities in information systems can occur at any time and there must be an emergency management to perceive the anomalies. Anomaly detection systems must not only find previously known anomalies, but also new unknown anomalies. The most effective solution to detect anomalies is self-learning based approaches. in this study, an anomaly detection system is proposed to be developed for file integration systems. The proposed system aims to provide a solution to information security problems that can be encountered in file integration systems.en_US
dc.description.sponsorshipIEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi Univen_US
dc.identifier.isbn978-1-5386-1501-0
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11454/70656
dc.identifier.wosWOS:000511448500226en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2018 26Th Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectanomaly detectionen_US
dc.subjectinformation securityen_US
dc.subjectmachine learningen_US
dc.subjectfile integrationen_US
dc.titleAn Anomaly Detection System Proposal to Ensure Information Security for File Integrationsen_US
dc.typeConference Objecten_US

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