IEEE Transactions on Cloud Computing · 2022 · 20 citations · 38 references
ComputingComputer ScienceInformation TechnologyCryptographyDatabasesStorage SystemsAttribute-based EncryptionData EncryptionData ProtectionPrivacy-preserving ProtocolsSecure Data SharingStorage SecurityBloom FiltersData AvailabilityPrivacy LeakageQuery PrivacyQuery Processing Over Encrypted DataSearch Over Encrypted DataSearchable EncryptionStorage Availability
Searchable encryption (SE) has emerged as a cryptographic primitive that allows data users to search on encrypted data. Most existing SE schemes usually delegate search operations to an intermediary such as a cloud server, which would inevitably result in single-point failure, privacy leakage, and even untrustworthy results. Several blockchain-based SE schemes have been proposed to alleviate these issues; however, they suffer from some issues, such as the support for multi-keyword multi-owner model, query privacy and data storage availability. In this paper, we propose BPMS, blockchain-based privacy-preserving multi-keyword search in multi-owner setting, which supports searching over encrypted data in trustworthy, private and efficient manners. The attribute Bloom filter has been introduced into our BPMS to build indexes, which protects query privacy and improves index generation performance. To guarantee data storage availability, our BPMS leverages the advantages of IPFS (InterPlanetary File System) to store large scale of encrypted data. Security proof and comparative analysis in theory indicate that our BPMS is more secure and efficient. A series of experiments conducted on a real-world dataset further demonstrate that our BPMS is feasible in practice.
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