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dc.contributor.authorBouyeddou, Benamar
dc.contributor.authorHarrou, Fouzi
dc.contributor.authorSun, Ying
dc.contributor.authorKadri, Benamar
dc.date.accessioned2019-04-08T07:08:54Z
dc.date.available2019-04-08T07:08:54Z
dc.date.issued2019-03-18
dc.identifier.citationBouyeddou B, Harrou F, Sun Y, Kadri B (2018) An Effective Network Intrusion Detection Using Hellinger Distance-Based Monitoring Mechanism. 2018 International Conference on Applied Smart Systems (ICASS). Available: http://dx.doi.org/10.1109/ICASS.2018.8652008.
dc.identifier.doi10.1109/ICASS.2018.8652008
dc.identifier.urihttp://hdl.handle.net/10754/631834
dc.description.abstractThis paper proposes an intrusion detection scheme for Denial Of Service (DOS) and Distributed DOS (DDOS) attacks detection. We used Hellinger distance (HD), which is an effective measure to quantify the similarity between two distributions, to detect the presence of potential malicious attackers. Specifically, we applied HD-based anomaly detection mechanism to detect SYN and ICMPv6-based DOS/DDOS attacks. Here, Shewhart chart is applied to HD to set up a detection threshold. The proposed mechanism is evaluated using DARPA99 and ICMPv6 traffic datasets. Results indicate that our mechanism accomplished reliable detection of DOS/DDOS flooding attacks.
dc.description.sponsorshipThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582. The authors (Benamar Bouyeddou and Benamar Kadri) would like to thank the STIC Lab, Department of Telecommunications, Abou Bekr Belkaid University for the continued support during the research.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8652008
dc.rightsArchived with thanks to 2018 International Conference on Applied Smart Systems (ICASS)
dc.subjectDARPA99 dataset
dc.subjectDOS/DDOS
dc.subjectHellinger distance
dc.subjectICMPv6 attacks
dc.subjectICMPv6 dataset
dc.subjectSYN flooding
dc.titleAn Effective Network Intrusion Detection Using Hellinger Distance-Based Monitoring Mechanism
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journal2018 International Conference on Applied Smart Systems (ICASS)
dc.conference.date2018-11-24 to 2018-11-25
dc.conference.name2018 International Conference on Applied Smart Systems, ICASS 2018
dc.conference.locationMedea, DZA
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Telecommunications, Abou Bekr Belkaid University, STIC Lab., Tlemcen, , Algeria
kaust.personHarrou, Fouzi
kaust.personSun, Ying
kaust.grant.numberOSR-2015-CRG4-2582
refterms.dateFOA2019-04-08T07:11:11Z
dc.date.published-online2019-03-18
dc.date.published-print2018-11


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