TY - GEN
T1 - Mobility-Aware RPL Network Assessment under a Blackhole Attack
AU - Ibrahimy, Saloua
AU - Lamaazi, Hanane
AU - Benamar, Nabil
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The speedy evolution of IoT technology is leading to a large-scale deployment of Low power and Lossy Networks (LLN). These constrained networks rely on tiny devices with limited computing and storage capabilities that connect to the internet using mainly the RPL routing protocol. However, this protocol can be an easy prey for attackers that can disrupt the network and degrade its performances by means of modification, isolation, or injection of malicious information. In this paper, we identify the impact of malicious nodes on mobile RPL-based networks by integrating a blackhole attack. The current study is benchmarked with static RPL networks in normal conditions. A set of routing metrics are evaluated, including resource consumption, control messages, and network stability. Our study highlights the degradation of network performances in a static environment compared to a mobile network in the presence of misbehaving (attackers) nodes.
AB - The speedy evolution of IoT technology is leading to a large-scale deployment of Low power and Lossy Networks (LLN). These constrained networks rely on tiny devices with limited computing and storage capabilities that connect to the internet using mainly the RPL routing protocol. However, this protocol can be an easy prey for attackers that can disrupt the network and degrade its performances by means of modification, isolation, or injection of malicious information. In this paper, we identify the impact of malicious nodes on mobile RPL-based networks by integrating a blackhole attack. The current study is benchmarked with static RPL networks in normal conditions. A set of routing metrics are evaluated, including resource consumption, control messages, and network stability. Our study highlights the degradation of network performances in a static environment compared to a mobile network in the presence of misbehaving (attackers) nodes.
KW - Blackhole Attack
KW - COOJA
KW - IoT
KW - LLNs
KW - Mobility Models
KW - RPL
UR - http://www.scopus.com/inward/record.url?scp=85146426818&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146426818&partnerID=8YFLogxK
U2 - 10.1109/3ICT56508.2022.9990638
DO - 10.1109/3ICT56508.2022.9990638
M3 - Conference contribution
AN - SCOPUS:85146426818
T3 - 2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022
SP - 541
EP - 546
BT - 2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022
Y2 - 20 November 2022 through 21 November 2022
ER -