Explainable artificial intelligence for digital forensics

EXplainable artificial intelligence (XAI) is an emerging research area relating to the creation of machine learning algorithms from which explanations for outputs are provided. In many fields, such as law enforcement, it is necessary that decisions made by and with the assistance of artificial intel...

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Vydáno v:WIREs. Forensic science Ročník 4; číslo 2; s. e1434 - n/a
Hlavní autoři: Hall, Stuart W., Sakzad, Amin, Choo, Kim‐Kwang Raymond
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 01.03.2022
Wiley Subscription Services, Inc
Témata:
Artificial intelligence
Computer forensics
Courts
Cybercrime
Decision making
digital artifacts
digital evidence
digital forensics
Efficacy
Evidence
EXplainable artificial intelligence
Forensic evidence
Forensic science
Intelligence
Law enforcement
Machine learning
Multimedia
Triage
ISSN:2573-9468, 2573-9468
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Popis
Shrnutí:EXplainable artificial intelligence (XAI) is an emerging research area relating to the creation of machine learning algorithms from which explanations for outputs are provided. In many fields, such as law enforcement, it is necessary that decisions made by and with the assistance of artificial intelligence (AI)‐based tools can be justified and explained to a human. We seek to explore the potential of XAI to further enhance triage and analysis of digital forensic evidence, using examples of the current state of the art as a starting point. This opinion letter will discuss both practical and novel ideas as well as controversial points for leveraging XAI to improve the efficacy of digital forensic (DF) analysis and extract forensically sound pieces of evidence (also known as artifacts) that could be used to assist investigations and potentially in a court of law. This article is categorized under: Digital and Multimedia Science > Artificial Intelligence Digital and Multimedia Science > Cybercrime Investigation XAI for Investigative Support.
Bibliografie:Sara Belkin, Executive Editor
Edited by
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ISSN:2573-9468
2573-9468
DOI:10.1002/wfs2.1434