AI in digital forensics: Ontology engineering for cybercrime investigations
Abstract
In parallel with the exponentially growing number of computing devices and IoT networks, the data storage and processing requirements of digital forensics are also increasing. Therefore, automation is highly desired in this field, yet not readily available, and many challenges remain, ranging from unstructured forensic data derived from diverse sources to a lack of semantics defined for digital forensic investigation concepts. By formally describing digital forensic concepts and properties, purpose‐designed ontologies enable integrity checking via automated reasoning and facilitate anomaly detection for the chain of custody in digital forensic investigations. This article provides a review of these ontologies, and investigates their applicability in the automation of processing traces of digital evidence.
RAS ID
32025
Document Type
Journal Article
Date of Publication
2020
School
School of Science / ECU Security Research Institute
Copyright
subscription content
Publisher
Wiley
Recommended Citation
Sikos, L. F. (2020). AI in digital forensics: Ontology engineering for cybercrime investigations. DOI: https://doi.org/10.1002/wfs2.1394
Comments
Sikos, L. F. (2020). AI in digital forensics: Ontology engineering for cybercrime investigations. WIREs Forensic Science, 3(3), article e1394. https://doi.org/10.1002/wfs2.1394