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Filtering estimated crime series based on route calculations on spatio-temporal data
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2017 (English)In: Proceedings - 2016 European Intelligence and Security Informatics Conference, EISIC 2016 / [ed] Brynielsson J.,Johansson F., Institute of Electrical and Electronics Engineers Inc. , 2017, 92-95 p.Conference paper (Refereed)
Abstract [en]

Law enforcement agencies strive to link serial crimes, most preferably based on physical evidence, such as DNA or fingerprints, in order to solve criminal cases more efficiently. However, physical evidence is more common at crime scenes in some crime categories than others. For crime categories with relative low occurrence of physical evidence it could instead be possible to link related crimes using soft evidence based on the perpetrators' modus operandi (MO). However, crime linkage based on soft evidence is associated with considerably higher error-rates, i.e. crimes being incorrectly linked. In this study, we investigate the possibility of filtering erroneous crime links based on travel time between crimes using web-based direction services, more specifically Google maps. A filtering method has been designed, implemented and evaluated using two data sets of residential burglaries, one with known links between crimes, and one with estimated links based on soft evidence. The results show that the proposed route-based filtering method removed 79 % more erroneous crimes than the state-of-the-art method relying on Euclidean straight-line routes. Further, by analyzing travel times between crimes in known series it is indicated that burglars on average have up to 15 minutes for carrying out the actual burglary event. © 2016 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2017. 92-95 p.
Keyword [en]
Crime filtering, Crime linkage, Route analysis, Travel time, Filtering method, Law-enforcement agencies, Modus operandi, Physical evidence, Route calculations, Spatio-temporal data, State-of-the-art methods, Crime
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-14132DOI: 10.1109/EISIC.2016.024ScopusID: 2-s2.0-85017255817ISBN: 9781509028566 (print)OAI: oai:DiVA.org:bth-14132DiVA: diva2:1091948
Conference
7th European Intelligence and Security Informatics Conference, EISIC 2016, 17 August 2016 through 19 August 2016
Available from: 2017-04-28 Created: 2017-04-28 Last updated: 2017-05-02Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
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More languages
Output format
  • html
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  • asciidoc
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