• L. William Mary
• M. Kannan
• K. Hema Aishwarya
• T. Ajisha

Abstract: Banking sector and Automated Teller Machine (ATM) system is one of the vital things to do deposit and withdrawal. Simultaneously, in the computerized world, cyber crime was also increasing day by day. This paper mainly focuses to secure the client’s account under the help of user’s body feature. Feature extraction (FE) is used here to reduce the feature’s dimensionality and also which is also used for various curvature processes. Nowadays cyber crime is also one of the main issues, because fraudsters are playing every place like schools, bank, companies, marketing places viz. Nowadays security problem is mostly occurring in the ATM mode. The current ATM system is secure, but still it has some small drawback like connection error during generating OTP. This paper, overtake this kind of security problem of the utilization of feature extraction methods to secure our bank account details as much as safely and confidentially from the fraudsters. For this issue, a new hybrid algorithm HFFE (Hybrid Facial Feature Extraction) has proposed.

Automated Teller Machine (ATM), Credit Card, HFFE algorithm, QR code, OTP, Image Processing.

"EATM: Hybrid Facial Feature Extraction Algorithm for Enhancing ATM Security System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.201-206, June 2019, Available :http://www.jetir.org/papers/JETIR1907D32.pdf

"EATM: Hybrid Facial Feature Extraction Algorithm for Enhancing ATM Security System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp201-206, June 2019, Available at : http://www.jetir.org/papers/JETIR1907D32.pdf