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Using exponentially weighted moving average algorithm to defend against DDoS attacks

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dc.contributor.author Machaka, P
dc.contributor.author Bagula, A
dc.contributor.author Nelwamondo, Fulufhelo V
dc.date.accessioned 2017-07-28T08:59:55Z
dc.date.available 2017-07-28T08:59:55Z
dc.date.issued 2016-11
dc.identifier.citation Machaka, P., Bagula, A. and Nelwamondo, F.V. 2016. Using exponentially weighted moving average algorithm to defend against DDoS attacks. 2016 International Conference on Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech), 30 November to 2 December 2016, Stellenbosch, South Africa, Cape Town. 10.1109/RoboMech.2016.7813157 en_US
dc.identifier.isbn 978-1-5090-3336-2
dc.identifier.uri http://ieeexplore.ieee.org/document/7813157/
dc.identifier.uri 10.1109/RoboMech.2016.7813157
dc.identifier.uri http://hdl.handle.net/10204/9316
dc.description 2016 International Conference on Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech), 30 November to 2 December 2016, Stellenbosch, South Africa, Cape Town en_US
dc.description.abstract This paper seeks to investigate the performance of the Exponentially Weighted Moving Average (EWMA) for mining big data and detection of DDoS attacks in Internet of Things (IoT) infrastructure. The paper will investigate the tradeoff between the algorithm’s detection rate, false alarm and detection delay. The paper seeks to further investigate how the performance of the algorithm is affected by the tuning parameters and how various network attack intensity affect its performance. The performance results are analyzed and discussed and further suggestion is also discussed. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;18352
dc.subject Change detection en_US
dc.subject Distributed denial of service en_US
dc.subject TCP-SYN flooding en_US
dc.subject Exponentially weighted moving average en_US
dc.subject EWMA en_US
dc.subject 2016 International Conference on Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech) en_US
dc.title Using exponentially weighted moving average algorithm to defend against DDoS attacks en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Machaka, P., Bagula, A., & Nelwamondo, F. V. (2016). Using exponentially weighted moving average algorithm to defend against DDoS attacks. IEEE. http://hdl.handle.net/10204/9316 en_ZA
dc.identifier.chicagocitation Machaka, P, A Bagula, and Fulufhelo V Nelwamondo. "Using exponentially weighted moving average algorithm to defend against DDoS attacks." (2016): http://hdl.handle.net/10204/9316 en_ZA
dc.identifier.vancouvercitation Machaka P, Bagula A, Nelwamondo FV, Using exponentially weighted moving average algorithm to defend against DDoS attacks; IEEE; 2016. http://hdl.handle.net/10204/9316 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Machaka, P AU - Bagula, A AU - Nelwamondo, Fulufhelo V AB - This paper seeks to investigate the performance of the Exponentially Weighted Moving Average (EWMA) for mining big data and detection of DDoS attacks in Internet of Things (IoT) infrastructure. The paper will investigate the tradeoff between the algorithm’s detection rate, false alarm and detection delay. The paper seeks to further investigate how the performance of the algorithm is affected by the tuning parameters and how various network attack intensity affect its performance. The performance results are analyzed and discussed and further suggestion is also discussed. DA - 2016-11 DB - ResearchSpace DP - CSIR KW - Change detection KW - Distributed denial of service KW - TCP-SYN flooding KW - Exponentially weighted moving average KW - EWMA KW - 2016 International Conference on Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech) LK - https://researchspace.csir.co.za PY - 2016 SM - 978-1-5090-3336-2 T1 - Using exponentially weighted moving average algorithm to defend against DDoS attacks TI - Using exponentially weighted moving average algorithm to defend against DDoS attacks UR - http://hdl.handle.net/10204/9316 ER - en_ZA


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