Visible to the public Detection and Prevention of Routing Attacks in Internet of Things

TitleDetection and Prevention of Routing Attacks in Internet of Things
Publication TypeConference Paper
Year of Publication2018
AuthorsChoudhary, S., Kesswani, N.
Conference Name2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
ISBN Number978-1-5386-4388-4
Keywords6LoWPAN, authentication techniques, CBA algorithm, Cluster-Based Algorithm, Clustering algorithms, composability, cryptography, encryption techniques, Internet, Internet of Things, Intrusion detection, intrusion detection system, Intrusion Detection System (IDS), IoT based network, Key Match Algorithm, MatLab simulation, message authentication, Protocols, pubcrawl, Resiliency, Routing, Routing attack, routing attack detection, routing attack prevention, RPL, security, Selective Forwarding, Sinkhole, smart network, smart objects, Trusted Computing

Internet of things (IoT) is the smart network which connects smart objects over the Internet. The Internet is untrusted and unreliable network and thus IoT network is vulnerable to different kind of attacks. Conventional encryption and authentication techniques sometimes fail on IoT based network and intrusion may succeed to destroy the network. So, it is necessary to design intrusion detection system for such network. In our paper, we detect routing attacks such as sinkhole and selective forwarding. We have also tried to prevent our network from these attacks. We designed detection and prevention algorithm, i.e., KMA (Key Match Algorithm) and CBA (Cluster- Based Algorithm) in MatLab simulation environment. We gave two intrusion detection mechanisms and compared their results as well. True positive intrusion detection rate for our work is between 50% to 80% with KMA and 76% to 96% with CBA algorithm.

Citation Keychoudhary_detection_2018