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Conference Paper: An information extraction framework for forensic investigations

TitleAn information extraction framework for forensic investigations
Authors
KeywordsInformation extraction
Named entity recognition
Relation extraction
Issue Date2015
PublisherSpringer New York LLC. The Journal's web site is located at http://www.springer.com/series/6102
Citation
The 11th Annual IFIP WG 11.9 International Conference on Digital Forensics (Advances in Digital Forensics XI), Orlando, FL., 26-28 January 2015. In IFIP Advances in Information and Communication Technology, 2015, v. 462, p. 61-76 How to Cite?
AbstractThe pervasiveness of information technology has led to an explosion of evidence. Attempting to discover valuable information from massive collections of documents is challenging. This chapter proposes a two-phase information extraction framework for digital forensic investigations. In the first phase, a named entity recognition approach is applied to the collected documents to extract names, locations and organizations; the named entities are displayed using a visualization system to assist investigators in finding coherent evidence rapidly and accurately. In the second phase, association rule mining is performed to identify the relations existing between the extracted named entities, which are then displayed. Examples include person-affiliation relations and organization-location relations. The effectiveness of the framework is demonstrated using the well-known Enron email dataset.
DescriptionThis series vol. entitled: Advances in Digital Forensics XI: 11th IFIP WG 11.9 International Conference, Orlando, FL, USA, January 26–28, 2015, Revised Selected Papers
Persistent Identifierhttp://hdl.handle.net/10722/219238
ISBN
ISSN
2015 SCImago Journal Rankings: 0.160
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYang, M-
dc.contributor.authorChow, KP-
dc.date.accessioned2015-09-18T07:18:31Z-
dc.date.available2015-09-18T07:18:31Z-
dc.date.issued2015-
dc.identifier.citationThe 11th Annual IFIP WG 11.9 International Conference on Digital Forensics (Advances in Digital Forensics XI), Orlando, FL., 26-28 January 2015. In IFIP Advances in Information and Communication Technology, 2015, v. 462, p. 61-76-
dc.identifier.isbn978-3-319-24122-7-
dc.identifier.issn1868-4238-
dc.identifier.urihttp://hdl.handle.net/10722/219238-
dc.descriptionThis series vol. entitled: Advances in Digital Forensics XI: 11th IFIP WG 11.9 International Conference, Orlando, FL, USA, January 26–28, 2015, Revised Selected Papers-
dc.description.abstractThe pervasiveness of information technology has led to an explosion of evidence. Attempting to discover valuable information from massive collections of documents is challenging. This chapter proposes a two-phase information extraction framework for digital forensic investigations. In the first phase, a named entity recognition approach is applied to the collected documents to extract names, locations and organizations; the named entities are displayed using a visualization system to assist investigators in finding coherent evidence rapidly and accurately. In the second phase, association rule mining is performed to identify the relations existing between the extracted named entities, which are then displayed. Examples include person-affiliation relations and organization-location relations. The effectiveness of the framework is demonstrated using the well-known Enron email dataset.-
dc.languageeng-
dc.publisherSpringer New York LLC. The Journal's web site is located at http://www.springer.com/series/6102-
dc.relation.ispartofIFIP Advances in Information and Communication Technology-
dc.rightsThe final publication is available at Springer via http://dx.doi.org/[insert DOI]-
dc.subjectInformation extraction-
dc.subjectNamed entity recognition-
dc.subjectRelation extraction-
dc.titleAn information extraction framework for forensic investigations-
dc.typeConference_Paper-
dc.identifier.emailChow, KP: kpchow@hkucc.hku.hk-
dc.identifier.authorityChow, KP=rp00111-
dc.identifier.doi10.1007/978-3-319-24123-4_4-
dc.identifier.scopuseid_2-s2.0-84951847223-
dc.identifier.hkuros255007-
dc.identifier.volume462-
dc.identifier.spage61-
dc.identifier.epage76-
dc.identifier.isiWOS:000364655200004-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151118-

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