Title: Detection of malicious packet dropping attacks in RPL-based internet of things

Authors: Sooyeon Shin; Kyounghoon Kim; Taekyoung Kwon

Addresses: Graduate School of Information, Yonsei University, 50 Yonsei-ro, Seoul, 03722, Republic of Korea ' Graduate School of Information, Yonsei University, 50 Yonsei-ro, Seoul, 03722, Republic of Korea ' Graduate School of Information, Yonsei University, 50 Yonsei-ro, Seoul, 03722, Republic of Korea

Abstract: The routing protocol for low-power and lossy networks (RPL) is an IPv6-based routing protocol optimised for internet of things (IoT) environments. However, it is susceptible to malicious packet dropping attacks. If a node with a lower rank that is closer to the root node attempts a malicious packet dropping, it may disrupt basic data transmission or even the entire IoT application service. In this paper, we present a novel detection method for malicious packet dropping attacks against RPL-based networks. The proposed method is based on the anomaly intrusion detection system and detects malicious packet dropping in the presence of normal packet losses. We evaluate the performance of the method on Contiki's network simulator, Cooja. The evaluation results show that the method has good performance in detecting malicious packet dropping attacks. In every case, the successful detection rate is greater than 94% and the false alarm rate is less than 3%.

Keywords: IoT; internet of things; IPv6; RPL; 6LowPAN; Packet Dropping; Detection; ContikiOS; Cooja simulator.

DOI: 10.1504/IJAHUC.2019.100085

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.31 No.2, pp.133 - 141

Received: 17 Mar 2017
Accepted: 14 Nov 2017
Published online: 07 Jun 2019 *

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