A Novel Detection Method for Grey Hole Attack in RPL
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Abstract
The Internet of Things (IoT) is a type of network that involves the Internet and things. This network consists of constrained devices that are connected through an IP protocol. In the IoT, a network with constrained devices is called 6LowPAN. RPL is a routing protocol to address the constraints and specific properties of these networks; though RPL puts the networks at risk through a large variety of attacks. The urgent need to develop secure routing solutions is required. In this paper, we investigated grey hole attacks and presented a detection method to identify and isolate the malicious node. The experiments show the proposed detection method improves PDR, Throughput and reduces PLR and E2ED in comparison with other scenarios.
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References
A. Shiranzaei and R. Z. & Khan, "Internet protocol versions—A review," in In 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), 2015.
J. Hui and P. Thubert, Compression format for IPv6 datagrams over IEEE 802.15. 4-based networks (No. rfc6282), 2011.
J. Jiang and Y. Liu, "Secure IoT routing: Selective forwarding attacks and trust-based defenses in RPL network," arXiv, 2022.
A. Shiranzaei and R. Z. Khan, "IPv6 Security Issues – A Systematic Review," in In 50th Golden Jubilee Annual Convention On Digital Life, 2015.
M. Marjanovi?, A. Antoni? and I. P. Žarko, "Edge computing architecture for mobile crowdsensing," Ieee access, 2018.
K. K. R. Choo, O. F. Rana and M. Rajarajan, "Cloud security engineering: Theory, practice and future research," IEEE Transactions on Cloud Computing, 2017.
Dr. V. Arthi. (2020). A Novel Channel Estimation Technique in MIMO-OFDM Mobile Communication Systems. International Journal of New Practices in Management and Engineering, 9(02), 08 - 14. https://doi.org/10.17762/ijnpme.v9i02.84
C. Wang, G. Liu, H. Huang, W. Feng, K. Peng and L. Wang, "MIASec: Enabling data indistinguishability against membership inference attacks in MLaaS," IEEE Transactions on Sustainable Computing, vol. 5, no. 3, pp. 365-376, 2019.
S. Raza, L. Wallgren and T. & Voigt, "SVELTE: Real-time intrusion detection in the Internet of Things," Ad hoc networks, vol. 11, no. 8, pp. 2661-2674, 2013.
D. C. Mehetre, S. E. Roslin and S. J. Wagh, "Detection and prevention of black hole and selective forwarding attack in clustered WSN with Active Trust," Cluster Computing, vol. 22, pp. 1313-1328, 2019.
T. Delkesh and M. A. Jabraeil Jamali, "EAODV: Detection and removal of multiple black hole attacks through sending forged packets in MANETs," Journal of Ambient Intelligence and Humanized Computing, vol. 10, pp. 1897-1914, 2019.
Martin, S., Wood, T., Hernandez, M., González, F., & Rodríguez, D. Machine Learning for Personalized Advertising and Recommendation. Kuwait Journal of Machine Learning, 1(4). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/156
A. J. C. Sunder and A. Shanmugam, "Jensen–Shannon divergence based independent component analysis to detect and prevent black hole attacks in healthcare WSN," Wireless Personal Communications, vol. 107, pp. 1607-1623, 2019.
M. A. Boudouaia, A. Abouaissa, A. Ali?Pacha, A. Benayache and P. Lorenz, "RPL rank based?attack mitigation scheme in IoT environment," International Journal of Communication Systems, vol. 34, no. 13, 2021.
S. Singh and H. S. Saini, "Learning-based security technique for selective forwarding attack in clustered WSN," Wireless Personal Communications, vol. 118, no. 1, pp. 789-814, 2021.
E. G. Ribera, B. M. Alvarez, C. Samuel, P. P. Ioulianou and V. G. Vassilakis, "Heartbeat-based detection of blackhole and greyhole attacks in RPL networks," in . In 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), 2020.
F. Osterlind, A. Dunkels, J. Eriksson, N. Finne and T. Voigt, "Cross-level sensor network simulation with cooja," in In Proceedings. 2006 31st IEEE conference on local computer networks , 2006.
G. Oikonomou, S. Duquennoy, A. Elsts, J. Eriksson, Y. Tanaka and N. Tsiftes, "The Contiki-NG open source operating system for next generation IoT devices," SoftwareX, 2022.