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A review of isolation attack mitigation mechanismsin RPL-Based 6LoWPAN of internet of things

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EN
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EN
The Routing Protocol for Low-Power and Lossy Networks (RPL) is an open standardrouting protocol defined by the Internet Engineering Task Force (IETF) to address theconstraints of IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). RPL issusceptible to various attacks, including isolation attacks, in which a node or a set of RPLnodes can be isolated from the rest of the network. Three significant isolation attacksare the black hole attack (BHA), selective forwarding attack (SFA), and destination ad-vertisement object (DAO) inconsistency attack (DAO-IA). In a BHA, a malicious nodedrops all packets intended for transmission silently. In an SFA, a malicious node forwardsonly selected packets and drops the other received packets. In a DAO-IA, a maliciousnode drops the received data packet and replies with a forwarding error packet, caus-ing the parent node to discard valid downward routes from the routing table. We reviewthe literature on proposed mechanisms, propose a taxonomy, and analyze the features,limitations, and performance metrics of existing mechanisms. Researchers primarily fo-cus on power consumption as the key performance metric when mitigating BHA (47%),SFA (51%), and DAO-IA (100%), with downward latency being the least addressed met-ric for BHA (4%) and SFA (3%), and control packet overhead being the least addressedfor DAO-IA (37%). Finally, we discuss the unresolved issues and research challenges inmitigating RPL isolation attacks.
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279--311
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Bibliogr. 67 poz., rys., tab.
Twórcy
autor
  • School of Computer Science and Engineering, Vellore Institute of Technology, India
Bibliografia
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  • 33. V. Neerugatti, A.R.M. Reddy, Detection and prevention of black hole attack in RPL Protocol based on the threshold value of nodes in the Internet of Things networks, International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(9S3): 325–329, 2019, doi: 10.35940/ijitee.I3060.0789S319.
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  • 35. C. Pu, Mitigating DAO inconsistency attack in RPL-based low power and lossy networks, [in:] 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, pp. 570–574, 2018, doi: 10.1109/CCWC.2018.8301614.
  • 36. I. Wadhaj, B. Ghaleb, C. Thomson, A. Al-Dubai, W.J. Buchanan, Mitigation mechanisms against the DAO attack on the routing protocol for low power and lossy networks (RPL), IEEE Access, 8: 43665–43675, 2020, doi: 10.1109/ACCESS.2020.2977476.
  • 37. R. Sahay, G. Geethakumari, B. Mitra, V. Thejas, Exponential smoothing based approach for detection of blackhole attacks in IoT, [in:] 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Indore, India, Vol. 2018, 2018, doi: 10.1109/ANTS.2018.8710073.
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  • 44. G. Soni, R. Sudhakar, A L-IDS against dropping attack to secure and improve RPL performance in WSN aided IoT, [in:] 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 377–383, 2020, doi: 10.1109/SPIN48934.2020.9071118.
  • 45. E.G. Ribera, B. Martinez Alvarez, C. Samuel, P.P. Ioulianou, V.G. Vassilakis, Heartbeatbased detection of blackhole and greyhole attacks in RPL networks, [in:] 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), Porto, Portugal, pp. 1–6, 2020, doi: 10.1109/CSNDSP49049.2020.9249519.
  • 46. L. Wallgren, S. Raza, T. Voigt, Routing attacks and countermeasures in the RPL-based Internet of Things, International Journal of Distributed Sensor Networks, 9(8): 794326, 2013, doi: 10.1155/2013/794326.
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  • 53. H.B. Patel, D.C. Jinwala, 6MID: Mircochain based intrusion detection for 6LoWPAN based IoT networks, Procedia Computer Science, 184: 929–934, 2021, doi: 10.1016/J.PROCS.2021.04.023.
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Bibliografia
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bwmeta1.element.baztech-ac56c2dc-c4d9-413a-b038-0948e40f31f9
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