Secured E-Commerce System using ECC and Multimodal Biometrics

Abstract

This paper focuses on the need to win electronic commerce customers trust by developing a secured electronic commerce system using elliptic curve cryptography (ECC) integrated with multimodal biometrics (iris and voice) as a methodology. Unlike the use of Rivest, Shamir and Adleman (RSA) algorithm that is commonly used in many computing devices to enforce the confidentiality of information, this research uses ECC, thereby reducing memory space complexity and computation power. Also, freed-up memory space is used to add other security measures in the form of iris and voice biometric to effect authentication. The mathematical expression of ECC was modified to reflect the encryption and decryption of image (iris) and audio (voice) data types integrated in the modeled secured electronic commerce system. Performance evaluation were carried out after implementation and results show a system that is promising by completing the processing of new user registration and logging in within 90 seconds. Although, the use of only RSA was discovered to occupy less space when the bit strings are less than 30 kilobyte, the methods-the integration of iris and voice biometrics into ECC (Sum iv) as used in this research consumes lesser memory, the moment the key-size is greater than 30 kilobyte, and increase the difficulty in eavesdropping through information traffic analysis and impersonating a customer with second and third line authentication measures.