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Collaborative Blockchain-Based Detection of Distributed Denial of Service Attacks Based on Internet of Things Botnets

Author

Listed:
  • Georgios Spathoulas

    (Department of Information Security and Communication Technology, Norwegian University of Science and Technology, 2815 Gjovik, Norway)

  • Nikolaos Giachoudis

    (Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece)

  • Georgios-Paraskevas Damiris

    (Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece)

  • Georgios Theodoridis

    (Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece)

Abstract

Internet of Things is one of the most significant latest developments in computer science. It is common for modern computing infrastructures to partially consist of numerous low power devices that are characterized by high diversity in both hardware and software. Existing security models, approaches and solutions are not able to sufficiently protect such systems. In this paper we propose the use of lightweight agents installed at multiple internet of things (IoT) installations (e.g., smart-homes), in order to collaboratively detect distributed denial of service (DDoS) attacks conducted by the use of IoT devices botnets. Specifically, agents exchange outbound traffic information in order to identify possible victims of DDoS attacks. This information exchange is governed by a blockchain smart contract, that ensures the integrity of both the procedure and the information. A simulation of the operation of the proposed methodology has been conducted in order to evaluate both its detection efficiency and its resilience against malicious agents that aim to falsify results.

Suggested Citation

  • Georgios Spathoulas & Nikolaos Giachoudis & Georgios-Paraskevas Damiris & Georgios Theodoridis, 2019. "Collaborative Blockchain-Based Detection of Distributed Denial of Service Attacks Based on Internet of Things Botnets," Future Internet, MDPI, vol. 11(11), pages 1-24, October.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:11:p:226-:d:280184
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    Citations

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    Cited by:

    1. Simon Nam Thanh Vu & Mads Stege & Peter Issam El-Habr & Jesper Bang & Nicola Dragoni, 2021. "A Survey on Botnets: Incentives, Evolution, Detection and Current Trends," Future Internet, MDPI, vol. 13(8), pages 1-43, July.
    2. Shatha Alharbi & Afraa Attiah & Daniyal Alghazzawi, 2022. "Integrating Blockchain with Artificial Intelligence to Secure IoT Networks: Future Trends," Sustainability, MDPI, vol. 14(23), pages 1-27, November.
    3. Kainat Ansar & Mansoor Ahmed & Markus Helfert & Jungsuk Kim, 2023. "Blockchain-Based Data Breach Detection: Approaches, Challenges, and Future Directions," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
    4. R. Akilandeswari & S. Malathi, 2022. "Design and implementation of controlling with preventing DDOS attacks using bitcoin by Ethereum block chain technology," Journal of Transportation Security, Springer, vol. 15(3), pages 281-297, December.

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