Artificial Intelligence Lab, Department of MIS, Univeristy of Arizona / Fear about identity verification reached new heights since the
terrorist attacks on Sept. 11, 2001, with national security issues
related to detecting identity deception attracting more interest
than ever before. Identity deception is an intentional falsification
of identity in order to deter investigations. Conventional investigation
methods run into difficulty when dealing with criminals
who use deceptive or fraudulent identities, as the FBI discovered
when trying to determine the true identities of 19 hijackers
involved in the attacks. Besides its use in post-event investigation,
the ability to validate identity can also be used as a tool to prevent
future tragedies. Here, we focus on uncovering patterns
of criminal identity deception
based on actual criminal records and
suggest an algorithmic approach to
revealing deceptive identities.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/106000 |
| Date | 03 1900 |
| Creators | Wang, Gang, Chen, Hsinchun, Atabakhsh, Homa |
| Publisher | ACM |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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