Behaver - Behavioural patterns verification for prevention of physical penetration using identity theft

Abstract

Nowadays every provider of critical infrastructure is obliged to use alarm systems - mainly simple surveillance CCTV cameras - to increase security and safety of those objects. Yet such systems have proven inefectual in preventing security disrupting situations, such as identity theft, as the most they can do is offer evidence to identify perpetrators of criminal acts once they have occurred. To use them for crime prevention, specially trained personnel need to monitor all screens constantly on the look-out for potentially dangerous activity - which is financially and time-consuming and prone to mistakes. This study aims at developing semi-automatic video surveillance technologies, which are able to detect events of changed behaviour of employees in relation to their standard behaviour - this means for example cases of identity theft, possible blackmail of a person, or safety disrupting cases - an employee might be sick or under influence of drugs what may lead to potentially dangerous acts.