A novel multi-user fingerprint minutiae based encryption and integrity verification for cloud data

Abstract

Data confidentiality and integrity are two major aspects that the cloud users need to consider while deploying data in the cloud. Traditional integrity techniques use cryptographic hash algorithms, but most of these hash algorithms are vulnerable to third party attacks. Traditional encryption algorithms such as advanced encryption standard (AES), fully homomorphic attribute based encryption (FHABE) and key policy attribute based encryption (KP-ABE) are failed to generate biometric based attributes and policies due to limited computing resources and memory. So, novel multi-user fingerprint minutiae with ciphertext-policy attribute based encryption for integrity verification and encryption (MFM-CP-ABE) model is proposed. MFM-CP-ABE model considers fingerprints of multiple users as attributes for encryption and also calculates integrity value. This model is the combination of multi-user fingerprint minutiae (MFM) extraction policy integrity method and improved ciphertext policy attribute based encryption (ICP-ABE) algorithm. This model is efficient in comparison to the traditional models in terms of encryption and decryption time and data size.