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Blockchain-Based IoT Forensics: Challenges and State-of-the-Art Frameworks

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Artificial Intelligence and Blockchain for Future Cybersecurity Applications

Part of the book series: Studies in Big Data ((SBD,volume 90))

Abstract

There is no doubt that the recent emergence of Internet of Things (IoT) paradigm brings significant changes in many aspects of our life including smart homes, smart cities, healthcare, farming, etc. Despite the unlimited advantages of IoTs, the tremendous increase of interconnected smart devices attracts more threats and hence introduces many challenges related to the security and digital forensics of the IoT environment. Although the IoT forensics is relatively new domain of research, several IoT forensics frameworks have been proposed recently to investigate cybercrimes. However, blockchain-based IoT forensics is the most promising approach. This chapter introduces the digital forensics from the point of view of IoT environment. It also discusses recent IoT forensics challenges and presents the most recently developed blockchain-based frameworks for the IoT forensic.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Kyungdong University, Gangwon-do, Republic of Korea

    Md Azam Hossain & Baseem Al-Athwari

Authors
  1. Md Azam Hossain
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  2. Baseem Al-Athwari
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Corresponding author

Correspondence to Md Azam Hossain .

Editor information

Editors and Affiliations

  1. Sultan Moulay Slimane University, Beni Mellal, Morocco

    Yassine Maleh

  2. Chouaib Doukkali University, El Jadida, Morocco

    Youssef Baddi

  3. Charles Darwin University, Canberra, Australia

    Mamoun Alazab

  4. Texas A&M University, San Antonio, USA

    Loai Tawalbeh

  5. Edinburgh Napier University, Edinburgh, UK

    Imed Romdhani

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Hossain, M.A., Al-Athwari, B. (2021). Blockchain-Based IoT Forensics: Challenges and State-of-the-Art Frameworks. In: Maleh, Y., Baddi, Y., Alazab, M., Tawalbeh, L., Romdhani, I. (eds) Artificial Intelligence and Blockchain for Future Cybersecurity Applications. Studies in Big Data, vol 90. Springer, Cham. https://doi.org/10.1007/978-3-030-74575-2_18

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