International Scientific Journal of Engineering and Management

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ISSN: 2583-6129

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Enhancing The ATM Transaction Security Using Iris Recognition Technology

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Enhancing The ATM Transaction Security Using Iris Recognition Technology

 

 

Shwetha K AssistantProfessor,

Department of Electronics and Communication Engineering, MaharajaInstituteofTechnology Mysore, Karnataka, India shwetha_ece@mitmysore.in

 

Maheshwari D

Department of Electronics and Communication Engineering, MaharajaInstituteofTechnology Mysore, Karnataka, India dharaneshkumar599@gmail.com

 

 Ananya M

Department of Electronics and Communication Engineering, MaharajaInstituteofTechnology Mysore, Karnataka, India ananya23suresh@gmail.com

 

      Abhiram Bharadwaj R

Department of Electronics and Communication Engineering,

MaharajaInstituteofTechnology Mysore, Karnataka, India abhirambharadwaj2004@gmail.com

 

Abhishek D

Department of Electronics and Communication Engineering, MaharajaInstituteofTechnology Mysore, Karnataka, India abhishekdevaprakash@gmail.com

 

 

Abstract—With the increasing use of electronic banking services, protecting the confidentiality and security of transactions conducted via ATMs has become a major priority. The current security system involving cards and Personal Identification Numbers makes them prone to risks of theft, card skimming, and shoulder surfing attacks. This paper describes the development of a new and improved secure system for conducting transactions at ATMs utilizing iris scanning technology with a biometric authentication process. The proposed biometric approach involves scanning the user’s iris image and identifying a match based on pre-stored templates with a Deep Learning Classifier. The uniqueness of irises makes them impervious to attacks or counterfeiting. The proposed system was tested with the IIT-Madras iris database with improved performance compared to the current security process. With its feasibility to perform transactions without requiring physical cards and memorized PIN codes, the proposed invention can be appropriately termed as next-generation ATMs.

Keywords —ATM Security, Iris Recognition, Biometric Authentication, Deep Learning, CNN, IIT Madras Iris Dataset, Financial Transaction Security, Pattern Recognition.


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