dc.contributor.author |
Burke, Ivan D
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dc.contributor.author |
Herbert, A
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dc.date.accessioned |
2020-09-07T11:34:48Z |
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dc.date.available |
2020-09-07T11:34:48Z |
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dc.date.issued |
2020-06 |
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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
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|
dc.identifier.uri |
https://www.academic-conferences.org/conferences/eccws/eccws-programme/
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dc.identifier.uri |
https://www.amazon.co.uk/Proceedings-European-Conference-Warfare-Security/dp/191276461X
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dc.identifier.uri |
http://hdl.handle.net/10204/11569
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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 |
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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 -
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en_ZA |