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AI in digital forensics: Ontology engineering for cybercrime investigations.

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Název: AI in digital forensics: Ontology engineering for cybercrime investigations.
Autoři: Sikos, Leslie F.
Zdroj: Wiley Interdisciplinary Reviews: Forensic Science; May/Jun2021, Vol. 3 Issue 3, p1-11, 11p
Témata: ARTIFICIAL intelligence, COMPUTER crimes, INTERNET of things, FORENSIC sciences, ONTOLOGIES (Information retrieval)
Abstrakt: 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. This article is categorized under:Digital and Multimedia Science > Artificial IntelligenceDigital and Multimedia Science > Cybercrime InvestigationDigital and Multimedia Science > Cyber Threat Intelligence [ABSTRACT FROM AUTHOR]
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Databáze: Biomedical Index
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Abstrakt: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. This article is categorized under:Digital and Multimedia Science > Artificial IntelligenceDigital and Multimedia Science > Cybercrime InvestigationDigital and Multimedia Science > Cyber Threat Intelligence [ABSTRACT FROM AUTHOR]
ISSN:25739468
DOI:10.1002/wfs2.1394