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Managing Suspicious Activity Reporting Systems at Small Agency Police Departments

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Author
Roberts, Bryan A.
Date
2012-09
Advisor
Miller, Patrick
Second Reader
Brannan, David
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Abstract
Law enforcement agencies have managed anonymous tip line programs for decades whereby community members can submit suspected criminal activity to their local law enforcement agency. As a result of the increasing threat of terrorism in the United States, suspicious activity reporting programs (SAR) accompany the traditional anonymous tip line. SARs include the reporting of suspicious behavior related to terrorism, as well as other criminal activity. SAR programs have been adopted by federal, state and local jurisdictions and at state and regional fusion centers. Homeland security is a shared responsibility of the American public and SAR programs are a mechanism that allows the public to contribute to this country’s security. Smaller law enforcement agencies in the United States lack the resources of larger police departments. The research set out to determine if smaller police agencies lacked SAR programs, which thus might create a gap in U.S. overall homeland security. An audit of 355 California police department websites that serve populations from 10,000 to over one million revealed that 5.9 per cent of the agencies supported an online SAR program. To verify the audit, 117 of the police departments were contacted and three of the agencies or 2.6 per cent supported a SAR program accessible by the public either by a direct phone line or by some other means. The thesis presents research to identify best practices for establishing SAR programs in police departments. The research explores national strategy documents, privacy and civil liberties guidelines and national SAR standards. The research identifies success stories of terrorist acts prevented because of a SAR. The research concludes with a list of action items agencies should consider when implementing a SAR program. Successful SAR programs rely on the timely analysis of information and sharing intelligence through shared networks.
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http://hdl.handle.net/10945/17447
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