A blockchain and smart contract-based data provenance collection and storing in cloud environment

Abstract

Data uploading needs security and privacy in the cloud. But there are some problems like centralized provenance data (PD) collection, storage, lack of security, integrity, and more time consumption. There are methods like Rabin, Knapsack, McEliece, Elagamal, and Rivest–Shamir–Adleman for the generation of keys but it increases the encryption and decryption time and less security. Therefore, the blockchain and smart contract-based data provenance (BSCDP) Architecture is proposed for providing secure storage in the cloud environment. Initially, the fingerprint biometrics and physically uncloneable functions (PUF) have been used in verification process. The combination of PUF and fingerprint biometrics is used for secure data transmission. To protect privacy and strengthen the security, the fuzzy extractor is employed. Secondly, we use an elliptic-curve key based cyclic shift transposition cryptography algorithm for enhancing the security when sharing the key. Thirdly, we introduce the blockchain and the interplanetary file system (IPFS) for PD collection, hash computation, and storing with reduced computational overhead (CO). The integrity of data is maintained by using blockchain based secure hashing algorithm-3. By arranging fuzzy based smart contracts (FSC), the data user (DU) tracks their data. FSC is employed for tracking the history of data. The data collected is directly stored in IPFS and the DU gets a hash from IPFS to retrieve the data in the future. Finally, the data verification is done by the provenance auditor. When comparing our proposed BSCDP method with existing methods, the proposed BSCDP method achieves high security in the cloud environment for 2 K users in terms of evidence insertion time (30 ms), verification time (30 ms), response time (40 ms), total change rate (5%), CO (5.8 Kb), encryption (50 ms) and decryption time (52 ms).