Investigation of Smart Machines with DNAs in SpiderNet

Mo Adda () and Nancy Scheidt ()
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Mo Adda: School of Computing, University of Portsmouth, University House Winston Churchill Ave, Portsmouth PO1 2UP, UK
Nancy Scheidt: Department of Policing, Criminology and Forensics, University of Winchester, Sparkford Road, Winchester SO22 4NR, UK

Future Internet, 2025, vol. 17, issue 2, 1-25

Abstract: The advancement of Internet of Things (IoT), robots, drones, and vehicles signifies ongoing progress, accompanied by increasing complexities and challenges in forensic investigations. Globally, investigators encounter obstacles when extracting evidence from these vast landscapes, which include diverse devices, networks, and cloud environments. Of particular concern is the process of evidence collection, especially regarding fingerprints and facial recognition within the realm of vehicle forensics. Moreover, ensuring the integrity of forensic evidence is a critical issue, as it is vulnerable to attacks targeting data centres and server farms. Mitigating these challenges, along with addressing evidence mobility, presents additional complexities. This paper introduces a groundbreaking infrastructure known as SpiderNet, which is based on cloud computing principles. We will illustrate how this architecture facilitates the identification of devices, secures the integrity of evidence both at its source and during transit, and enables investigations into individuals involved in criminal activities. Through case studies, we will demonstrate the potential of SpiderNet to assist law enforcement agencies in addressing crimes perpetrated within IoT environments.

Keywords: heterogeneous devices autonomous; smart machines; evidence preservation; IoT forensics; SpiderNet (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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