Data Warehousing - Coplink*/BorderSafe/RISC

* The COPLINK system was initially developed by the University of Arizona Artificial Intelligence Lab with funding from the National Institute of Justice and the National Science Foundation since 1997. With additional venture funding and product development, Knowledge Computing Corporation (KCC) currently distributes, maintains, and updates the commercially available COPLINK Solution Suite.

Introduction

This project aims to develop automated deception detection techniques using data mining approaches. At current stage, we focus on the problem of criminal identity deception that is frequently encountered by police officers during crime investigations. In the mean time, individual identity is central to the practice of intelligence communities. We believe that a solution to that problem will not only help solving crimes in local law enforcement, but also benefit a larger domain of the homeland security.

With the help of a police detective expert in Tucson Police Department (TPD) who has served in law enforcement for 30 years, we conducted a case study on a sample of deceptive criminal identity records. We found that identity deception mostly occurred in the attributes of name, date of birth, ID numbers, and address. A taxonomy of criminal identity deception was built to show different deception characteristics in different identity attributes. We developed an automated detection algorithm using string comparison techniques. Experiments showed that the proposed algorithm correctly detected 94% of deceptive criminal identities.

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Screenshots

The following figure shows when an officer enters a name, date of birth, SSN and address of a suspect, the Deception Detection algorithm returns a list of names found in the police databases that could be the same person. The officer can have more results returned by increasing the agreement level using the slider.

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