Paper 2020/1094

TN-IDS for Network Layer Attacks in RPL based IoT Systems

Ambili K N and Jimmy Jose

Abstract

Routing protocol for Low power and lossy network (RPL) is a standardized optimal protocol for routing in Internet of Things (IoT). The constrained wireless sensor network in IoT is characterized by lack of processing speed, low power and low memory. Sometimes various network attacks enabling the RPL network affect the network performance dismally. This leads to drastic variation in energy consumption at nodes and disturb the RPL network protocol structure. This leads to reduced processing speed and memory allocation in the network. We first illustrate the attacks and their impact in RPL network by simulation. To detect such attacks, we propose an Intrusion Detection System (IDS) scheme for RPL network based on trust computation. Trust based Neighbor notification IDS (TN-IDS) is a secure hierarchical distribution system which monitors the network intrusion and checks the performance of the network. The new TN-IDS system will track all nodes in the network and identify the malicious nodes. The activity list prepared by IDS indicates them to a sink node. This is achieved by introducing a distributed leader election algorithm to collect metrics related to the RPL network. Hence, the performance metrics of the RPL network together with TN-IDS module can identify the malicious node and isolate them.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Preprint. MINOR revision.
Keywords
IoTRPLDoSblackholeTopology attackssinkholeIDSwormhole
Contact author(s)
ambili_p180002cs @ nitc ac in
jimmy @ nitc ac in
History
2020-09-15: received
Short URL
https://ia.cr/2020/1094
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2020/1094,
      author = {Ambili K N and Jimmy Jose},
      title = {{TN}-{IDS} for Network Layer Attacks in {RPL} based {IoT} Systems},
      howpublished = {Cryptology {ePrint} Archive, Paper 2020/1094},
      year = {2020},
      url = {https://eprint.iacr.org/2020/1094}
}
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