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Tracking botnets on Nation Research and Education Network

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dc.contributor.author Burke, Ivan D
dc.contributor.author Herbert, A
dc.date.accessioned 2020-09-07T11:34:48Z
dc.date.available 2020-09-07T11:34:48Z
dc.date.issued 2020-06
dc.identifier.citation Burke, I.D. and Herbert, A. 2020. Tracking botnets on Nation Research and Education Network. Proceedings of the 19th European Conference on Cyber Warfare and Security, A Virtual Conference Hosted By The University of Chester, United Kingdom, 25-26 June 2020, 10pp en_US
dc.identifier.uri https://www.academic-bookshop.com/ourshop/cat_1643278-2020-Conferences.html
dc.identifier.uri https://www.academic-conferences.org/conferences/eccws/eccws-programme/
dc.identifier.uri https://www.amazon.co.uk/Proceedings-European-Conference-Warfare-Security/dp/191276461X
dc.identifier.uri http://hdl.handle.net/10204/11569
dc.description Copyright: 2020 Academic Conferences International (ACI). This is the fulltext version of the work. en_US
dc.description.abstract The South African National Research and Education Network (SANREN) proves network connectivity and services to all tertiary education networks and research councils within South Africa. The NREN forms part of South Africa’s national integrated cyber infrastructure, as such, it is a potential target for cyber-attacks. Due to the large volume of traffic and decentralised nature of the SA NREN, monitoring, reporting and mitigating cyber-attacks is a complex problem. The NREN Cyber Incident Response Team (CSIRT) uses network flow data to identify early indicators of cyber-attacks. In this paper the focus will be on the mechanisms used to identify malicious botnet traffic using network flow analysis. en_US
dc.language.iso en en_US
dc.publisher Academic Conferences International (ACI) en_US
dc.relation.ispartofseries Worklist;23659
dc.subject Network flow analysis en_US
dc.subject Nation Research and Education Network en_US
dc.subject NREN en_US
dc.subject Botnet detection en_US
dc.subject Cyber threat detection en_US
dc.subject Network traffic analysis en_US
dc.subject South African National Research and Education Network en_US
dc.subject SANREN en_US
dc.title Tracking botnets on Nation Research and Education Network en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Burke, I. D., & Herbert, A. (2020). Tracking botnets on Nation Research and Education Network. Academic Conferences International (ACI). http://hdl.handle.net/10204/11569 en_ZA
dc.identifier.chicagocitation Burke, Ivan D, and A Herbert. "Tracking botnets on Nation Research and Education Network." (2020): http://hdl.handle.net/10204/11569 en_ZA
dc.identifier.vancouvercitation Burke ID, Herbert A, Tracking botnets on Nation Research and Education Network; Academic Conferences International (ACI); 2020. http://hdl.handle.net/10204/11569 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Burke, Ivan D AU - Herbert, A AB - The South African National Research and Education Network (SANREN) proves network connectivity and services to all tertiary education networks and research councils within South Africa. The NREN forms part of South Africa’s national integrated cyber infrastructure, as such, it is a potential target for cyber-attacks. Due to the large volume of traffic and decentralised nature of the SA NREN, monitoring, reporting and mitigating cyber-attacks is a complex problem. The NREN Cyber Incident Response Team (CSIRT) uses network flow data to identify early indicators of cyber-attacks. In this paper the focus will be on the mechanisms used to identify malicious botnet traffic using network flow analysis. DA - 2020-06 DB - ResearchSpace DP - CSIR KW - Network flow analysis KW - Nation Research and Education Network KW - NREN KW - Botnet detection KW - Cyber threat detection KW - Network traffic analysis KW - South African National Research and Education Network KW - SANREN LK - https://researchspace.csir.co.za PY - 2020 T1 - Tracking botnets on Nation Research and Education Network TI - Tracking botnets on Nation Research and Education Network UR - http://hdl.handle.net/10204/11569 ER - en_ZA


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