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Biometrics Being Weighed in Fraud Fight.(Technology)(Brief article)


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Author:enhanced due diligence countries    the extent of transaction monitoring depends on

Keywords:identity fraud identity,    knowledge based authentication,    id verification as a service,    '+id +recognition,    kyc guidelines,  cdd edd sdd


Biometric liveness detection based on cross modal fusion
Nowadays, the banking and financial systems have been totally changed due to the environment and globalization changes and competition of business services. Internet Banking or Web Banking is used to describe banking transactions through internet application. Internet Banking means user can get connected to his bank's website with personal computer system and web browser. But there are many security problems like fraudulent websites, fake emails from banks, capturing user IDs and passwords, hacking personal bank accounts and steal money etc. To overcome these problems, this gives a solution with a Fingerprint biometric.
The state-of-the-art technologies of security systems adopting Biometric methodologies for effectively authenticating the user. These security systems rely on the biometric characteristics/data taken from the user for authentication. Unfortunately such biometric data is stolen or duplicated by the imposters/unauthorized users. Most of the biometrics systems depend purely on identifying the physiological characteristics of the user. It becomes easier to spoof in these biometric systems with the aid of fake biometric; it further reduces the reliability and security of biometric system. Liveness detection using the facial features also has been receiving more attention compared to other biometric modalities. In this paper, prevention of spoof attack in biometric system is employed by detecting the liveness of the user with the help of local facial features like eye blinking, lip movement, forehead and chin movement pattern of the face detected with real-time generic web-camera. The developed system is evaluated for 50 users, with severe variation in pose and expressions. With the Indian face database, face recognition accuracy is around 87% and with own database face recognition accuracy is around 86% and Liveness detection performance for authenticated users is around 88% is achieved.

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