NDLI: Flow-based anomaly detection using semisupervised learning

Content Provider	IEEE Xplore Digital Library
Author	Jadidi, Z. Muthukkumarasamy, V. Sithirasenan, E. Singh, K.
Copyright Year	2015
Description	Author affiliation: Sch. of Inf. & Commun. Technol., Griffith Univ., Gold Coast, QLD, Australia (Jadidi, Z.; Muthukkumarasamy, V.; Sithirasenan, E.; Singh, K.)
Abstract	In recent years, flow-based anomaly detection has been used as a scalable method for high-speed networks. The application of supervised learning in flow-based anomaly detection has been considered in a number of studies. However, supervised methods are not very useful as they are only trained with labelled data. Therefore, in this study, we use a semi-supervised method to address the problem of the limitation of labelled data. S4VM is a semi-supervised method which can work with both labelled and unlabelled data. This method is used in this study to detect anomalies in flow traffic. The results show that S4VM has high accuracy when a large proportion of data is unlabelled. Although the accuracy of S4VM is slightly less than supervised learning, this method reduces the cost of labeling data, as only a small number of labelled flows are required. To evaluate the proposed anomaly detection method, a number of flow-based datasets are generated.
Starting Page	1
Ending Page	5
File Size	246383
Page Count	5
File Format	PDF
e-ISBN	9781467381185
DOI	10.1109/ICSPCS.2015.7391760
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-14
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Cloud computing Particle separators Supervised learning supervised learning Detectors flow traffic anomaly detection Classification algorithms semi-supervised learning Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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