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A survey of DDoS attacking techniques and defence mechanisms in the IoT network

Author

Listed:
  • Ruchi Vishwakarma

    (National Institute of Technology, Kurukshetra)

  • Ankit Kumar Jain

    (National Institute of Technology, Kurukshetra)

Abstract

Internet-of-things has emerged out as an important invention towards employing the tremendous power of wireless media in the real world. We can control our surroundings by interacting with numerous smart applications running independently on different platforms, almost everywhere in the world. IoT, with such a ubiquitous popularity often serve itself as a potential platform for escalating malicious entities. These entities get an access to the legitimate devices by exploiting IoT vulnerabilities which results from several constraints like limited resources, weaker security, etc. and can further take form of various attacks. Distributed Denial-of-service (DDoS) in IoT network is an attack which targets the availability of the servers by flooding the communication channel with impersonated requests coming from distributed IoT devices. Defending DDoS in IoT has now become an exigent area of research due to the recent incidents of demolishment of some renowned servers, reported in previous few years. In this paper, we discuss the concept of malware and botnets working behind ‘Distributed’ DoS in IoT. The various DDoS defence techniques are broadly described and compared in order to identify the security gaps present in them. Moreover, we list out the open research issues and challenges that need to be addressed for a stronger as well as smarter DDoS defence.

Suggested Citation

  • Ruchi Vishwakarma & Ankit Kumar Jain, 2020. "A survey of DDoS attacking techniques and defence mechanisms in the IoT network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(1), pages 3-25, January.
    • Handle: RePEc:spr:telsys:v:73:y:2020:i:1:d:10.1007_s11235-019-00599-z
    DOI: 10.1007/s11235-019-00599-z
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    Citations

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    Cited by:

    1. 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.
    2. Radwa Ahmed Osman & Sherine Nagy Saleh & Yasmine N. M. Saleh & Mazen Nabil Elagamy, 2021. "A Reliable and Efficient Tracking System Based on Deep Learning for Monitoring the Spread of COVID-19 in Closed Areas," IJERPH, MDPI, vol. 18(24), pages 1-20, December.
    3. Li Duan & Jingxian Zhou & You Wu & Wenyao Xu, 2022. "A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems," International Journal of Distributed Sensor Networks, , vol. 18(3), pages 15501477211, March.

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