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Mobilising artificial intelligence to identify patterns of criminal behaviour on digital devices

The explosion of digital devices, online services and social media platforms along with increasingly larger hard disk drive capacities have contributed to digital forensic practitioners facing an ever-growing volume of digital data to review and investigate. Alongside this expanding ecosystem of digital data, operating systems and tools, the Forensic Science Regulators, globally and in the UK, are looking to ensure that digital forensic practice is based on validated processes and tools.

For some years now, police forces throughout the UK are reported as being overwhelmed by a huge backlog of digital devices waiting to be examined, threatening to undermine the effectiveness of the criminal justice system. A recent Freedom of Information request to all police forces in the UK revealed over 20,000 digital devices are queued for analysis nationally (Long, 2022). The Metropolitan Police Service who in 2020 stated 60% of devices take at least 3 months to be examined, whilst most of the remainder take up to a year to be analysed (Metropolitan Police, 2020). Attempts to address this has seen police forces use triage techniques to target items of priority, but this is a subjective process and subject to variation based on experience.

The aim of this PhD is to explore how neuro-symbolic AI techniques, machine learning (ML) and artificial intelligence (AI) might be operationalised together with criminological theory, such as crime scripting, to understand how patterns or signature for different types of criminal offences might be identified and flagged for analysis by digital forensic practitioners.



  • Educational or professional background in digital forensics, cyber security, or AI
  • Scripting and/or coding experience
  • Willingness to learn appropriate programming languages to develop ML models/AI


Study mode

Full-time or part-time


Background reading

Dehghanniri, H. and Borrion, H., 2021. Crime scripting: A systematic review. European Journal of Criminology18(4), pp.504-525.

Du, X., Hargreaves, C., Sheppard, J., Anda, F., Sayakkara, A., Le-Khac, N.A. and Scanlon, M., 2020, August. SoK: exploring the state of the art and the future potential of artificial intelligence in digital forensic investigation. In Proceedings of the 15th International Conference on Availability, Reliability and Security (pp. 1-10).

Jeong, D., 2020. Artificial intelligence security threat, crime, and forensics: Taxonomy and open issues. IEEE Access8, pp.184560-184574.

Long, J, 2022. Police backlog of over 20,000 digital devices awaiting examination. Available online: (Accessed: 05/12/2022)

Metropolitan Police, 2020, Digital Device awaiting forensic examination, Freedom of information request reference no: 01.FOI.20.013431. Available online: (Accessed: 05/12/2022)



Dr Ian Kennedy

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