Law enforcement agencies (LEAs) globally are facing high demand to view, process, and analyse digital evidence. Arrests for Indecent Images of Children (IIOC) have risen by a factor of 25 over the previous decade. A case typically requires the use of computing resources for between 2-4 weeks. The lengthy time is due to the sequential ordering of acquiring a forensically sound copy of all data, systematically extracting all images, before finally analysing each to automatically identify instances of known IIOC images (second-generation) or manually identifying new images (first-generation). It is therefore normal practice that an understanding of the image content is only obtained right at the end of the investigative process. A reduction in processing time would have a transformative impact, by enabling timely identification of victims, swift intervention with perpetrators to prevent re-offending, and reducing the traumatic psychological effects of any ongoing investigation for the accused and their families.

In this paper, a new approach to the digital forensic processes containing suspected IIOC content is presented, whereby in-process metrics are used to prioritise case handling, ensuring cases with a high probability of containing IIOC content are prioritised. The use of automated planning (AP) enables a systematic approach to case priorisation. In this paper, a planning approach is presented where AP is used to generate investigative actions in 60-minute segments, before re-planning to account for discoveries made during the execution of planned actions. A case study is provided consisting of 5 benchmark cases, demonstrating on average a reduction of 36% in processing time and a 26% reduction in time required to discover IIOC content.
Original languageEnglish
Title of host publicationProceedings of the Thirty-third International Conference on Automated Planning and Scheduling
Subtitle of host publication(ICAPS 2023)
EditorsSven Koenig, Roni Stern, Mauro Vallati
PublisherAAAI press
Number of pages9
ISBN (Print)1577358813, 9781577358817
Publication statusPublished - 2 Jul 2023
Event33rd International Conference on Automated Planning and Scheduling - Charles University, Prague, Czech Republic
Duration: 8 Jul 202313 Jul 2023
Conference number: 33

Publication series

NameProceedings of the International Conference on Automated Planning and Scheduling
PublisherAAAI Press
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843


Conference33rd International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2023
Country/TerritoryCzech Republic
Internet address


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