@article{Dr. D. Bennet_2022, title={A Novel Liveness Detection System for Biometric Authentication System Using Random Forest and Texture-Gray Level Features}, url={http://thedesignengineering.com/index.php/DE/article/view/8825}, abstractNote={<p>The term itself determines to an automated recognition system which identifies an individual with his biological behavioral characteristics. It is primarily used for the security purpose which indeed is used in forensic and commercial applications. Here, the biological behavioral characteristics comprise of various traits such as the face, iris, voice, fingerprint, gaits etc. In this, the fingerprints are considered to be the most determined because of its uniqueness and it can never be identical to another. Also, they retain the same without any change throughout the time period. In biometrics, there are vulnerable shortcomings such as they are fragile to some attacks namely spoofing which refers to the fraudulent action by an unauthorized person to a biometric system with fake inputs that generate authorized person’s input. Henceforth it is important to detect the spoof, to this, the proposed paper describes an easy to integrate and inexpensive technique or methodology to improvise the security through fingerprints scanners. Our primary aim in this research is to develop an improved fingerprint spoofing detection system. We use random forest classifier for classification</p&gt;}, number={1}, journal={Design Engineering}, author={Dr. D. Bennet , M. Saravanan,}, year={2022}, month={Jan.}, pages={520-530} }