The UNSW-NB15 dataset 2021-11-26T10:34:04Z 2021-11-26T10:34:04Z 2019 en_US
dc.description.abstract The raw network packets of the UNSW-NB 15 dataset was created by the IXIA PerfectStorm tool in the Cyber Range Lab of the Australian Centre for Cyber Security (ACCS) for generating a hybrid of real modern normal activities and synthetic contemporary attack behaviours. Tcpdump tool is utilised to capture 100 GB of the raw traffic (e.g., Pcap files). This data set has nine types of attacks, namely, Fuzzers, Analysis, Backdoors, DoS, Exploits, Generic, Reconnaissance, Shellcode and Worms. The Argus, Bro-IDS tools are used and twelve algorithms are developed to generate totally 49 features with the class label. en_US
dc.language English
dc.language.iso EN en_US
dc.rights GPL en_US
dc.rights.uri en_US
dc.subject.other UNSW-NB15 dataset en_US
dc.title The UNSW-NB15 dataset en_US
dc.type Dataset en_US
dcterms.accessRights open access
dcterms.accrualMethod Design a decent dataset for evaluating network anomaly detection system. en_US
dcterms.rights Free use of the UNSW-NB15 dataset for academic research purposes is hereby granted in perpetuity. Use for commercial purposes is strictly prohibited. Nour Moustafa and Jill Slay have asserted their rights under the Copyright. en_US
dcterms.rightsHolder Copyright 2015, University of New South Wales en_US
dspace.entity.type Dataset en_US
unsw.contributor.researchDataCreator Moustafa, Nour en_US
unsw.coverage.temporalFrom 2015-09-30 en_US
unsw.description.storageURL en_US
unsw.description.storageURL en_US
unsw.description.storageURL en_US
unsw.identifier.doi en_US
unsw.isPublicationRelatedToDataset en_US
unsw.isPublicationRelatedToDataset en_US
unsw.isPublicationRelatedToDataset en_US
unsw.isPublicationRelatedToDataset Deep Neural Networks for Network Intrusion Detection
unsw.relation.OriginalPublicationAffiliation Moustafa, Nour, Sch of Engineering & IT (Sum), UNSW Canberra, en_US
unsw.relation.faculty UNSW Canberra
unsw.relation.fundingAgency school of Engineering and Information Technology- Canberra en_US
unsw.relation.fundingScheme A funding for a PhD scheme, relates to design an effective anomaly detection system en_US
unsw.relation.projectDesc A TFS scholarship for a student PhD to designing novel statitcal anomaly Detection system, be able to apply online and adaptive with detecting zero-day attacks en_US
unsw.relation.projectEndDate 2017-05-03 en_US
unsw.relation.projectStartDate 2014-08-07 en_US
unsw.relation.projectTitle A TFS scholarship for a student PhD to designing novel anomaly Detection system en_US School of Engineering and Information Technology
unsw.subject.SEOcode 940301 Defence and Security Policy en_US
unsw.subject.fieldofresearchcode 080303 Computer System Security en_US
Resource type