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Identification of IoT devices for forensic investigation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

As the Internet of Things (IoT) environment rapidly grows, so do the distribution and utilisation of IoT devices as well as Cyber-Enabled and Dependent Crime activities. This leads to challenges investigators face when forensically investigating the IoT to present evidence in the court of law. Current tools and frameworks demonstrate a variety of limitations which need to be improved to efficiently deal with IoT forensics. In this article, we introduce a novel approach to uniquely identify IoT devices to improve IoT Forensics while introducing new terms, such as the DNA and Genes of devices. These novel terms for a dynamic and complex environment, such as the IoT, will ease the understanding of unique device identifiers due to its well-known association with traditional crime scene investigation. To elaborate on the importance of unique device identification we establish the context of the IoT, its Forensic Investigation and challenges as well as the approach of Universal Identification Numbers utilising Set Theory. Additionally, we consider the implementation within our proposed IoT Server model environment to demonstrate the necessity in IoT Forensics.
Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE 10th International Conference on Intelligent Systems (IS)
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-7281-5456-5
ISBN (Print)978-1-7281-5457-2
Publication statusPublished - 18 Sep 2020
Event2020 IEEE 10th International Conference on Intelligent Systems - Varna, Bulgaria
Duration: 28 Aug 202030 Aug 2020

Publication series

NameProceedings of the 2020 IEEE 10th International Conference on Intelligent Systems (IS)
ISSN (Print)1541-1672


Conference2020 IEEE 10th International Conference on Intelligent Systems


  • Identification_of_IoT_devices_for_Forensic_Investigation_IEEE_Conference

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    Accepted author manuscript (Post-print), 221 KB, PDF document

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