IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v73y2020i1d10.1007_s11235-019-00599-z.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-019-00599-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-019-00599-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:73:y:2020:i:1:d:10.1007_s11235-019-00599-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.