Masengo Wa Umba, SAbu-Mahfouz, Adnan MIRamotsoela, TDHancke, GP2019-10-172019-10-172019-06Masengo Wa Umba, S. et al. 2019. A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network. In: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), Vancouver, BC, Canada, 12-14 June 2019978-1-7281-3666-0 978-1-7281-3667-7978-1-7281-3666-0https://ieeexplore.ieee.org/abstract/document/8781458DOI: 10.1109/ISIE.2019.8781458http://hdl.handle.net/10204/11174Presented at: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), Vancouver, BC, Canada, 12-14 June 2019. Copyright: 2019 SPIE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website.Wireless communications and Wireless Sensor Networks (WSNs) are intensively used in manufacturing industries, in medical devices, for the determination of the position and for the guidance of military drones and bombs. Given the scope of utilization of WSNs, the security of wireless communications is a very critical problem that must be tackled accordingly. A Software-Defined Wireless Sensor Network (SDWSN) is realized by infusing a Software Defined Network (SDN) model in a WSN. In this paper, the cryptography schemes as well as the security threats related to SDWSNs are identified and the Artificial Intelligence (AI) techniques used to detect intrusions in SDWSNs are presented. It is shown that a two-level security model combining cryptography schemes and AI techniques can be used to fight malicious attacks against SDWSNs.enArtificial IntelligenceIntrusion detectionSoftware-Defined Wireless Sensor NetworkWireless Sensor NetworksConference PresentationMasengo Wa Umba, S., Abu-Mahfouz, A. M., Ramotsoela, T., & Hancke, G. (2019). A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network. IEEE. http://hdl.handle.net/10204/11174Masengo Wa Umba, S, Adnan MI Abu-Mahfouz, TD Ramotsoela, and GP Hancke. "A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network." (2019): http://hdl.handle.net/10204/11174Masengo Wa Umba S, Abu-Mahfouz AM, Ramotsoela T, Hancke G, A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network; IEEE; 2019. http://hdl.handle.net/10204/11174 .TY - Conference Presentation AU - Masengo Wa Umba, S AU - Abu-Mahfouz, Adnan MI AU - Ramotsoela, TD AU - Hancke, GP AB - Wireless communications and Wireless Sensor Networks (WSNs) are intensively used in manufacturing industries, in medical devices, for the determination of the position and for the guidance of military drones and bombs. Given the scope of utilization of WSNs, the security of wireless communications is a very critical problem that must be tackled accordingly. A Software-Defined Wireless Sensor Network (SDWSN) is realized by infusing a Software Defined Network (SDN) model in a WSN. In this paper, the cryptography schemes as well as the security threats related to SDWSNs are identified and the Artificial Intelligence (AI) techniques used to detect intrusions in SDWSNs are presented. It is shown that a two-level security model combining cryptography schemes and AI techniques can be used to fight malicious attacks against SDWSNs. DA - 2019-06 DB - ResearchSpace DP - CSIR KW - Artificial Intelligence KW - Intrusion detection KW - Software-Defined Wireless Sensor Network KW - Wireless Sensor Networks LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-3666-0 978-1-7281-3667-7 SM - 978-1-7281-3666-0 T1 - A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network TI - A review of artificial intelligence based intrusion detection for Software-Defined Wireless Sensor Network UR - http://hdl.handle.net/10204/11174 ER -