MONITORING AND PREDICTING PHYSICAL FORCE ATTACKS ON TRANSACTION TERMINALS

Abstract: visual features of a vehicle, a vehicle's orientation with respect to a transaction terminal, and an individual associated with the vehicle are derived from video captured of the terminal and a surrounding area of the terminal. additional information associated with brute force attacks in a location associated with the terminal are obtained as additional features. the visual features and the additional features are provided as input to a trained machine-learning model (mlm) and the mlm provides as output a confidence value representing a prediction as to whether the current vehicle and the current individual are potentially about to engage in a brute force attack on the terminal. when the confidence value exceeds a threshold value, enhanced feature detection is enabled on the video, external systems are notified, and an incident packet of information is assembled.

Inventor(s): Jodessiah Sumpter, Christopher John Costello, Matthew Robert Burris, Gregory Joseph Hartl, Caleb Wayne Martinez

CPC Classification: G07F19/207 ({Automatic teller machines [ATMs]})

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