Blockchain-Driven Conjunctive Keyword Searchable Technique Over Encrypted Data for Cloud-Based Cyber Physical Social Systems

Abstract

Cyber-physical-social (CPS) systems require searchable encryption (SE) to safeguard sensitive data before storing it in the cloud. Existing dynamic searchable symmetric encryption (DSSE) methods have problems with index creation, document updates that lose data, and search speed. These issues must be addressed to develop an efficient CPS system. Therefore, we have developed a new approach that integrates a DSSE protocol with a blockchain-based data management system, thereby establishing a secure and efficient method for managing encrypted data. We make sure that past data remains private and that we can quickly search through data by building a forward index with a special pseudorandom function (PRF) and checking it with symmetric encryption. Keeping the encrypted index on a private distributed ledger and the secret data on a public ledger reduces storage and speeds up transaction processing. To enhance data privacy and access verification, an additional authentication system must prevent unauthorized access to the private blockchain. Authorization systems verify access permissions and execute the outcomes. Performance evaluation shows that the proposed solution improves the integrity of encrypted data and the speed of queries in the Chicago Crime and Enron Email datasets. The proposed method used only 0.68 MB client and 121.4 MB servers, builds in 121.4 s, updates in 156.4 for client and 167.2 ms for server, and outperforms all in speed, storage, and efficiency. The results are also checked for correctness and originality at the same time to reduce the complexity and computational cost by 60% and 70%, respectively, for modern cyber-physical social applications. Finally, the proposed method improves existing methods based on an extensive evaluation of Chicago Crime and Enron Email datasets, and can benefit modern CPS systems.