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...

Full description

Saved in:
Bibliographic Details
Published in:WIREs. Forensic science Vol. 4; no. 2; pp. e1434 - n/a
Main Authors: Hall, Stuart W., Sakzad, Amin, Choo, Kim‐Kwang Raymond
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.03.2022
Wiley Subscription Services, Inc
Subjects:
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
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract 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.
AbstractList 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.
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 IntelligenceDigital and Multimedia Science > Cybercrime Investigation
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
Author Hall, Stuart W.
Choo, Kim‐Kwang Raymond
Sakzad, Amin
Author_xml – sequence: 1
  givenname: Stuart W.
  surname: Hall
  fullname: Hall, Stuart W.
  organization: Monash University
– sequence: 2
  givenname: Amin
  orcidid: 0000-0003-4569-3384
  surname: Sakzad
  fullname: Sakzad, Amin
  email: amin.sakzad@monash.edu
  organization: Monash University
– sequence: 3
  givenname: Kim‐Kwang Raymond
  orcidid: 0000-0001-9208-5336
  surname: Choo
  fullname: Choo, Kim‐Kwang Raymond
  organization: University of Texas at San Antonio
BookMark eNp9kEFLAzEQhYNUsNYe_AcLnjxsm8km2e1RSqtCwYOKxzBNZ0tKzNZkpfbfu7UeRNDTPJjvvWHeOeuFJhBjl8BHwLkY7-okRiALecL6QpVFPpG66v3QZ2yY0oZ3LEhRqqrPJrOPrUcXcOkpw9i62lmHPnOhJe_dmoKlrG5itnJr13aLTlNIzqYLdlqjTzT8ngP2PJ89Te_yxcPt_fRmkVshSpkTRyJZagRCElhKEFDACoVFKGoNSJWuAFZKVbDUqElJCxVOdCU5ghbFgF0dc7exeXun1JpN8x5Dd9IIXZSKl0oXHXV9pGxsUopUm210rxj3Brg5lGMO5ZhDOR07_sXa7rXWNaGN6Px_jp3ztP872rzMH8WX4xPcS3a-
CitedBy_id crossref_primary_10_1109_ACCESS_2022_3204171
crossref_primary_10_3390_jimaging9010003
crossref_primary_10_1002_widm_70015
crossref_primary_10_3390_buildings13051213
crossref_primary_10_1016_j_fsigen_2023_102994
crossref_primary_10_1109_ACCESS_2023_3324403
crossref_primary_10_3390_electronics11121903
crossref_primary_10_51583_IJLTEMAS_2025_1407000002
Cites_doi 10.1109/CVPR42600.2020.01446
10.1109/MSEC.2019.2925649
10.1109/CVPR.2018.00357
10.1016/j.inffus.2019.12.012
10.1007/s10472-019-09632-y
10.1177/1365712718807226
10.1177/2053951715622512
10.52922/ti180697
10.1145/3407023.3407068
10.1109/TII.2019.2947432
10.1007/978-3-030-58592-1_24
10.1145/3290605.3300831
ContentType Journal Article
Copyright 2021 Wiley Periodicals LLC.
2022 Wiley Periodicals LLC.
Copyright_xml – notice: 2021 Wiley Periodicals LLC.
– notice: 2022 Wiley Periodicals LLC.
DBID AAYXX
CITATION
8BJ
FQK
JBE
DOI 10.1002/wfs2.1434
DatabaseName CrossRef
International Bibliography of the Social Sciences (IBSS)
International Bibliography of the Social Sciences
International Bibliography of the Social Sciences
DatabaseTitle CrossRef
International Bibliography of the Social Sciences (IBSS)
DatabaseTitleList
International Bibliography of the Social Sciences (IBSS)
CrossRef
DeliveryMethod fulltext_linktorsrc
EISSN 2573-9468
EndPage n/a
ExternalDocumentID 10_1002_wfs2_1434
WFS21434
Genre article
GroupedDBID 1OC
1VH
33P
34L
AAHQN
AAMNL
AANLZ
AAXRX
ACAHQ
ACCZN
ACXBN
ADOZA
AEIGN
AEUYR
AFFPM
AHBTC
AITYG
ALMA_UNASSIGNED_HOLDINGS
ALVPJ
AMYDB
DCZOG
DRFUL
DRSTM
LATKE
LEEKS
MEWTI
M~E
WXSBR
0R~
AAYXX
AGYGG
ALUQN
CITATION
8BJ
FQK
JBE
ID FETCH-LOGICAL-c2274-e0aee476a1eae2a7412131da2ca13f61ae86811d5581b6a6e54c18a96840a1623
IEDL.DBID DRFUL
ISICitedReferencesCount 19
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000904724800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2573-9468
IngestDate Wed Nov 12 17:12:18 EST 2025
Sat Nov 29 05:56:25 EST 2025
Tue Nov 18 22:15:27 EST 2025
Wed Jan 22 16:25:38 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 2
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c2274-e0aee476a1eae2a7412131da2ca13f61ae86811d5581b6a6e54c18a96840a1623
Notes Sara Belkin, Executive Editor
Edited by
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0001-9208-5336
0000-0003-4569-3384
PQID 2637507563
PQPubID 4669295
PageCount 11
ParticipantIDs proquest_journals_2637507563
crossref_primary_10_1002_wfs2_1434
crossref_citationtrail_10_1002_wfs2_1434
wiley_primary_10_1002_wfs2_1434_WFS21434
PublicationCentury 2000
PublicationDate March/April 2022
2022-03-00
20220301
PublicationDateYYYYMMDD 2022-03-01
PublicationDate_xml – month: 03
  year: 2022
  text: March/April 2022
PublicationDecade 2020
PublicationPlace Hoboken, USA
PublicationPlace_xml – name: Hoboken, USA
– name: Hoboken
PublicationTitle WIREs. Forensic science
PublicationYear 2022
Publisher John Wiley & Sons, Inc
Wiley Subscription Services, Inc
Publisher_xml – name: John Wiley & Sons, Inc
– name: Wiley Subscription Services, Inc
References 2016; 3
2019; 86
2020; 12368
2020
2021; 17
2019; 23
2019; 69
2009
2019; 17
2019
2018
2020; 58
2020; 47
2017
2016
2014
Aditya K. (e_1_2_11_2_1) 2018
e_1_2_11_10_1
e_1_2_11_14_1
e_1_2_11_13_1
e_1_2_11_12_1
e_1_2_11_11_1
e_1_2_11_6_1
e_1_2_11_28_1
e_1_2_11_5_1
e_1_2_11_27_1
e_1_2_11_4_1
e_1_2_11_26_1
e_1_2_11_3_1
National Research Council (e_1_2_11_23_1) 2009
e_1_2_11_21_1
e_1_2_11_20_1
e_1_2_11_25_1
e_1_2_11_24_1
e_1_2_11_9_1
e_1_2_11_8_1
e_1_2_11_22_1
e_1_2_11_18_1
e_1_2_11_16_1
e_1_2_11_15_1
Kafadar K. (e_1_2_11_17_1) 2019; 69
e_1_2_11_19_1
(e_1_2_11_7_1) 2020; 47
References_xml – start-page: 1250
  year: 2018
  end-page: 1255
– start-page: 1
  year: 2019
  end-page: 15
– start-page: 3389
  year: 2018
  end-page: 3398
– volume: 47
  start-page: 23
  year: 2020
  end-page: 48
  article-title: Foundations of explainable knowledge‐enabled systems
  publication-title: Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges
– year: 2009
– volume: 58
  start-page: 82
  year: 2020
  end-page: 115
  article-title: Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
  publication-title: Information Fusion
– volume: 86
  start-page: 193
  issue: 1–3
  year: 2019
  end-page: 229
  article-title: Digital forensics and investigations meet artificial intelligence
  publication-title: Annals of Mathematics and Artificial Intelligence
– volume: 12368
  start-page: 396
  year: 2020
  end-page: 413
– year: 2020
– volume: 3
  issue: 1
  year: 2016
  article-title: How the machine “thinks”: Understanding opacity in machine learning algorithms
  publication-title: Big Data & Society
– volume: 69
  start-page: 6
  year: 2019
  article-title: Statistics and the impact of the 2009 NAS report
  publication-title: Duke LJ Online
– volume: 17
  start-page: 74
  issue: 5
  year: 2019
  end-page: 77
  article-title: Artificial intelligence for law enforcement: Challenges and opportunities
  publication-title: IEEE Security Privacy
– start-page: 14441
  year: 2020
  end-page: 14450
– year: 2017
– year: 2016
– year: 2018
– volume: 17
  start-page: 971
  issue: 2
  year: 2021
  end-page: 979
  article-title: Semantic learning based cross‐platform binary vulnerability search for iot devices
  publication-title: IEEE Transactions on Industrial Informatics
– year: 2014
– volume: 23
  start-page: 255
  issue: 3
  year: 2019
  end-page: 262
  article-title: Determining authenticity of video evidence in the age of artificial intelligence and in the wake of deepfake videos
  publication-title: The International Journal of Evidence & Proof
– start-page: 1250
  volume-title: 2018 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/12th IEEE International Conference on Big Data Science and Engineering (Trustcom/Bigdatase)
  year: 2018
  ident: e_1_2_11_2_1
– ident: e_1_2_11_8_1
  doi: 10.1109/CVPR42600.2020.01446
– ident: e_1_2_11_26_1
  doi: 10.1109/MSEC.2019.2925649
– ident: e_1_2_11_3_1
  doi: 10.1109/CVPR.2018.00357
– ident: e_1_2_11_4_1
  doi: 10.1016/j.inffus.2019.12.012
– ident: e_1_2_11_13_1
– volume-title: Strengthening forensic science in the United States: A path forward
  year: 2009
  ident: e_1_2_11_23_1
– ident: e_1_2_11_16_1
– ident: e_1_2_11_24_1
– volume: 69
  start-page: 6
  year: 2019
  ident: e_1_2_11_17_1
  article-title: Statistics and the impact of the 2009 NAS report
  publication-title: Duke LJ Online
– ident: e_1_2_11_21_1
– ident: e_1_2_11_9_1
  doi: 10.1007/s10472-019-09632-y
– ident: e_1_2_11_10_1
– volume: 47
  start-page: 23
  year: 2020
  ident: e_1_2_11_7_1
  article-title: Foundations of explainable knowledge‐enabled systems
  publication-title: Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges
– ident: e_1_2_11_19_1
  doi: 10.1177/1365712718807226
– ident: e_1_2_11_12_1
– ident: e_1_2_11_5_1
  doi: 10.1177/2053951715622512
– ident: e_1_2_11_6_1
– ident: e_1_2_11_20_1
– ident: e_1_2_11_15_1
– ident: e_1_2_11_25_1
  doi: 10.52922/ti180697
– ident: e_1_2_11_11_1
  doi: 10.1145/3407023.3407068
– ident: e_1_2_11_28_1
– ident: e_1_2_11_14_1
  doi: 10.1109/TII.2019.2947432
– ident: e_1_2_11_18_1
  doi: 10.1007/978-3-030-58592-1_24
– ident: e_1_2_11_27_1
  doi: 10.1145/3290605.3300831
– ident: e_1_2_11_22_1
SSID ssj0002142758
Score 2.2915416
Snippet EXplainable artificial intelligence (XAI) is an emerging research area relating to the creation of machine learning algorithms from which explanations for...
SourceID proquest
crossref
wiley
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage e1434
SubjectTerms 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
Title Explainable artificial intelligence for digital forensics
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fwfs2.1434
https://www.proquest.com/docview/2637507563
Volume 4
WOSCitedRecordID wos000904724800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2573-9468
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002142758
  issn: 2573-9468
  databaseCode: M~E
  dateStart: 20190101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVWIB
  databaseName: Wiley Online Library Full Collection 2020
  customDbUrl:
  eissn: 2573-9468
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002142758
  issn: 2573-9468
  databaseCode: DRFUL
  dateStart: 20190101
  isFulltext: true
  titleUrlDefault: https://onlinelibrary.wiley.com
  providerName: Wiley-Blackwell
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NS8MwFH_sw4MXP1BxOkcRD17KmqRNEzyJrniYQ9ThbiVNUhmMKevUm3-7Sb82QUHwlsNr2iTvNb-E934_gDOquCABwS6R0hxQQoJcpmTipqlnFjnxcKJyEtdhOBqxyYTfNeCiqoUp-CHqCzcbGfn_2ga4SLL-ijT0I82wiXPiN6GNjd_6LWhf30fjYX3FYtnEwlyh0_glsWLyrOIW8nC_fv77jrSCmetgNd9tou1_fecObJUg07ksvGIXGnq-B9ym25W1Uo51mII7wpmukXI6BsI6avpslURs22a3y2wfxtHg8erGLYUTXInNKdPVntDaD6lAWmgsDGjAiCAlsBSIpBQJzShDSAWBAa1UUB34EjHBLfGLQAYQHUBr_jLXh-DIUAVp4gtmuvIT7PEEc8l5SgLFhM9lB86ryYtlySpuxS1mccGHjGM7_tiOvwOntelrQaXxk1G3WoG4jKYsxpQYYBMGlJjX5XP9ewfxU_SAbePo76bHsIltVUOeWtaF1nLxpk9gQ74vp9miV7pVD5q3n4MvvGLRIw
linkProvider Wiley-Blackwell
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8MwED_mJuiLH6g4nVrEB1-KTdKkCfgi6phYh-iGeytpmspApqxT_32Tfm2CguBbHi5pPu6aX4673wGcsERIQgl2iVLmgRIQ5PJExW6aeuaQYw_HSU7iGgb9Ph-NxH0DzqtcmIIfona4WcvI_9fWwK1D-mzOGvqZZtgYOvGXoOUbNaJNaF09dIdh7WOxdGJBXqLTKCax1eR5RS7k4bO6__craY4zF9Fqft101_830Q1YK2Gmc1HoxSY09GQLhA24K7OlHKsyBXuEM16g5XQMiHWS8bOtJWLbNr5dZdsw7F4PLntuWTrBVdi8M13tSa39gEmkpcbSwAaMCEokVhKRlCGpOeMIJZQa2Mok09RXiEthqV8kMpBoB5qT14neBUcFCU1jX3IzlB9jT8RYKCFSQhMufaHacFrtXqRKXnFb3uIlKhiRcWTXH9n1t-G4Fn0ryDR-EupURxCV9pRFmBEDbQLKiPlcvtm_DxA9dR-xbez9XfQIVnqDuzAKb_q3-7CKbY5DHmjWgeZs-q4PYFl9zMbZ9LDUsS9XodPi
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3PS8MwFA5zE_HiD1ScTi3iwUuxSZo0AS_iLIpjDHW4W0iTVAYyxzr13zfpr01QELzl8Jo2yXvNl_De9wFwRjWXmGDkY6XsASXC0GdaJX6aBnaRkwAlOidx7UX9PhuN-KABLqtamIIfor5wc5GR_69dgJupTi8WrKGfaYZsoONwBbRCwqkNy1b3IR726jsWRycW5RKd1jGxU5NnFblQgC7q579vSQucuYxW8-0m3vzfh26BjRJmeleFX2yDhpnsAO4S7spqKc-5TMEe4Y2XaDk9C2I9PX5xWiKu7fLbVbYLhvHN0_WtX0on-ArZc6ZvAmlMGFEJjTRIWtiAIIZaIiUhTimUhlEGoSbEwlYqqSGhgkxyR_0ioYVEe6A5eZuYfeCpSJM0CSWzXYUJCniCuOI8xUQzGXLVBufV7AlV8oo7eYtXUTAiI-HGL9z42-C0Np0WZBo_GXWqJRBlPGUCUWyhTUQotq_LJ_v3DsRz_Ihc4-DvpidgbdCNRe-uf38I1pErccjzzDqgOZ-9myOwqj7m42x2XLrYFyO-010
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Explainable+artificial+intelligence+for+digital+forensics&rft.jtitle=WIREs.+Forensic+science&rft.au=Hall%2C+Stuart+W&rft.au=Amin+Sakzad&rft.au=Kim%E2%80%90Kwang+Raymond+Choo&rft.date=2022-03-01&rft.pub=Wiley+Subscription+Services%2C+Inc&rft.issn=2573-9468&rft.eissn=2573-9468&rft.volume=4&rft.issue=2&rft.spage=e1434&rft_id=info:doi/10.1002%2Fwfs2.1434&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2573-9468&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2573-9468&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2573-9468&client=summon