Target vehicle identification for border safety using mutual information

Abstract

The security of border and transportation systems is a critical component of the national strategy for homeland security. The security concerns at the border are not independent of law enforcement in border-area jurisdictions because information known by local law enforcement agencies may provide valuable leads useful for securing the border and transportation infrastructure. The combined analysis of law enforcement information and data generated by vehicle license plate readers at the international borders can be used to identify suspicious vehicles at ports of entry. This not only generates better quality leads for border protection agents but may also serve to reduce wait times for commerce, vehicles, and people as they cross the border. In this paper we use the mutual information concept to identify vehicles that frequently cross the border with vehicles that are involved in criminal activity. We find that the mutual information measure can be used to identify vehicles that can be potentially targeted at the border.