A security hybrid mechanism using fuzzy with adaptive ElGamal approach in cloud

Abstract

SummaryDue to the increasing number of people accessing their personal medical information online, it has raised concerns about the security of their data. Unauthorized access to patient's records can lead to disclosure of their privacy. There are various types of frauds that can affect the integrity of a patient's records such as theft of identity and tax fraud. It is therefore necessary to implement a secure data access and retrieval system in order to prevent these types of crimes. Security passwords are often the only barrier between hackers and users. Many of us often use the same ones for multiple accounts. Biometric passwords are more secure than traditional ones due to their ability to be created by observing a person's eyes. They can also be created with a secret key that's stored in an encrypted format. Proposed method combines a secure key with an optimized fuzzy extraction algorithm to provide high‐level security. The file is then encrypted using adaptive ElGamal and its digital signature is uploaded in cloud. Data recovery services are also introduced to help users keep their data secure using seed block algorithm (SBA). These services can be utilized to recover files once they get lost or get destroyed. The proposed security approach for back‐up files (SBA) can be used to minimize the time it takes for the recovery process. It also addresses the issue of unauthorized access to the data stored on remote servers.