A comparative study of spatio-temporal hotspot analysis techniques in security informatics

Abstract

Security informatics is an emerging field of study focusing on the development and evaluation of advanced information technologies and systems for national and homeland security-related applications. Spatio-temporal hotspot analysis is an important component of security informatics since location and time are two critical aspects of most security-related events. The outputs of such analyses can provide useful information to guide the activities aimed at preventing, detecting, and responding to security problems. This paper reports a computational study carried out to evaluate the effectiveness of two prominent spatio-temporal hotspot analysis techniques, i.e., scan statistics and risk-adjusted clustering, in two selected security-related applications including infectious disease informatics and crime analysis. This paper also proposes a new technique based on support vector machines. Preliminary experiments have demonstrated positively that this new approach can be a viable analysis alternative in security informatics.