Visible to the public Detection of malicious nodes in NDN VANET for Interest Packet Popple Broadcast Diffusion Attack

TitleDetection of malicious nodes in NDN VANET for Interest Packet Popple Broadcast Diffusion Attack
Publication TypeConference Paper
Year of Publication2017
AuthorsZhang, X., Li, R., Zhao, W., Wu, R.
Conference Name2017 11th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)
Date Publishedoct
PublisherIEEE
ISBN Number978-1-5386-0533-2
KeywordsAnalytical models, Human Behavior, Interest Packet Popple Broadcast Diffusion Attack, Internet, Markov chain, Markov processes, Mitigation strategy, Named Data Network Security, named data networking, NDN VANET, next generation networks, packet popple broadcast diffusion attack, PBDA, Ports (Computers), Predictive models, pubcrawl, resilience, Resiliency, Roads, Scalability, telecommunication security, vehicular ad hoc networks, Vehicular Ad-hoc Network
Abstract

As one of the next generation network architectures, Named Data Networking(NDN) which features location-independent addressing and content caching makes it more suitable to be deployed into Vehicular Ad-hoc Network(VANET). However, a new attack pattern is found when NDN and VANET combine. This new attack is Interest Packet Popple Broadcast Diffusion Attack (PBDA). There is no mitigation strategies to mitigate PBDA. In this paper a mitigation strategies called RVMS based on node reputation value (RV) is proposed to detect malicious nodes. The node calculates the neighbor node RV by direct and indirect RV evaluation and uses Markov chain predict the current RV state of the neighbor node according to its historical RV. The RV state is used to decide whether to discard the interest packet. Finally, the effectiveness of the RVMS is verified through modeling and experiment. The experimental results show that the RVMS can mitigate PBDA.

URLhttps://ieeexplore.ieee.org/document/8285755/
DOI10.1109/ICASID.2017.8285755
Citation Keyzhang_detection_2017