Paper Title
A Secure Multiplicative Homomorphic Facial Biometrics Encryption Technique

Abstract
Facial Biometrics have become an effective means of authenticity and identity verification because of its capability of matching and recognizing a human face. These biometrics are basically the measurements/physical characteristics of an individual. Innovative methods to protect sensitive facial biometric data are required in light of the growing privacy and data security issues. Homomorphic Encryption is a technique where operations like addition, multiplication are performed on encrypted data without decrypting it. The paper proposes a homomorphic encryption technique on the facial biometric datasets in order to ensure and maintain the confidentiality and also integrity of the data during the storage and computation. The proposed work demonstrates how the multiplicative homomorphic encryption scheme is applied on to the real time datasets and how the addition and multiplication operations are carried out on the encrypted data. By applying this technique on to the facial biometrics data, we can address the privacy issues and improve the accuracy and efficiency by introducing a new privacy-preserving facial biometric system. Keywords - Biometrics, Facial Biometrics, Homomorphic Encryption, Security, Cloud