Biometric authentication utilizing fuzzy extractor with PSO based security ensuring the data security mechanism as Trio in Cloud

Abstract

Cloud computing is widely preferred by various organizations due to its numerous advantages such as lower costs, better security, and faster processing times. The most critical data stored in the remote servers are protected by firewalls and encryption, at the same time, the user’s essential data may be accessed from the remote cloud server without their control. This kind of data storage facility introduces various security complications. In order to prevent these issues, we have proposed a method that uses a Biometric authentication method with PSO to provide high-level security. The method combines a pseudo-integer authentication scheme with a secret OTP that can be used to authenticate an individual. A Tri-level security mechanism model is proposed to store three types of data classification namely, No Privacy, Privacy with Trusted Provider and Privacy with Non-PNR. The proposed method provides a uniform security scheme for all the classifications using Adaptive ElGamal with Menezes-Qu-Verstone, that prevents data loss and corruption caused by insiders in the cloud. Further Seed Block is utilized to recover and extract data without loss. It does so by effectively extracting the data from the formatted disks. It is then followed with the decryption process, as if the data are requested by the user. Our framework aims to provide a secure and authenticated environment for accessing data. It features an improved authentication process and reduced complexity.