Suspect Vehicle Identification for Border Safety with Modified Mutual Information
作者： Siddharth Kaza , Yuan Wang , Hsinchun Chen
DOI: 10.1007/11760146_27
关键词: Homeland security 、 Mutual information 、 Computer science 、 Heuristics 、 Computer security 、 Heuristic 、 Vehicle identification 、 Suspect 、 Border crossing 、 Jurisdiction
摘要: The Department of Homeland Security monitors vehicles entering and leaving the country at land ports entry. Some are targeted to search for drugs other contraband. Customs Border Protection agents believe that involved in illegal activity operate groups. If criminal links one vehicle known then their border crossing patterns can be used identify partner vehicles. We perform this association analysis by using mutual information (MI) pairs potentially activity. Domain experts also suggest may cross certain times day evade inspection. propose modify formulation include heuristic cross-jurisdictional data from border-area jurisdictions. find modified MI with time heuristics performs better than classical identifying
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