 Robust intrusion detection system based on fuzzy C means clustering scheme implemented in IoT-based wireless sensor networksM. Ezhilarasi and V. Krishnaveni International Journal of Networking and Virtual Organisations, 2020, vol. 23, issue 4, 312-326 Abstract: Research in wireless networks and communication protocols have reached new heights in recent times with the advent of state-of-the-art communication techniques and gadgets. They have found widespread utility in recent times especially with the advent of cloud computing and internet of things (IoT). IoTs offer immense potential in today's scenario aiding in smart computing and automation of things focused to making life of consumers easier and simpler. However, security of information transmitted and received over wireless networks is an essential concern to preserve privacy and authenticity of information. This research issue is however quite complex as it involves security of bulk information quite private and confidential to be delivered in a wireless medium prone to hackers. This research article has investigated the various issues related to security of IoT-based wireless sensor networks and proposed a fuzzy-based clustering algorithm to effectively detect an intrusion and make the information secure. Keywords: wireless sensor networks; intrusion detection systems; internet of things; IoT; fuzzy clustering. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:23:y:2020:i:4:p:312-326 Access Statistics for this article More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.