Technologies for developing an advanced intelligent ATM with self-defence capabilities

Abstract

We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

Self-Payment Fraud Detection on Automated Teller Machine

“…There are methods to detect illegal objects, such as cameras and card reproducers, attached to ATM [7]. Also, in [8] proposed a system to detect criminal objects attached to ATM like cameras that could read the users' password. To prevent password theft in [9] diversifies password entering methods to avoid another people looking from behind of user.…”

“…To prevent password theft in [9] diversifies password entering methods to avoid another people looking from behind of user. In [8] a system developed which warn user when loiterers are behind the customer. To detect and prevent financial transactions made by inappropriate methods or users there are methods such as card holder identification via biometrics [6,10,11], forged note detection in ATM environment [6,9] and recording facial images of ATM users [5,12,13].…”