Preventing Cloud Attacks using Bio-Metric Authentication in Cloud Computing

Abstract

Objectives: To provide a secured and efficient solution for end users to access their personal files in the cloud servers using biometric authentication. Methods/: In this Minutiae Map (MM) algorithm is implemented for processing fingerprint based authentication. The user personal files are stored in free public multiple cloud storages namely Dropbox and CloudMe using splitting and merging techniques. RC4 algorithm is used to improve the security in cloud environment. Cross site request forgery (CSRF) and Cross site scripting (XSS) prevention techniques are used to provide security against cloud attacks. Findings: This study analyses that MM algorithm is the best accurate fingerprint feature extraction algorithm compared to Orientation Map, Gabor Filter and core point detection techniques. The proposed approach measures the user personal files upload time in cloud servers namely Dropbox and CloudMe. The study also analyses the presence of CSRF and XSS attacks in the application. Applications/ Improvements: The proposed system can be improvised involving preventive measures for more security threats and integrating other biometric authentications.