Privacy-Preserving Dynamic Multi-Keyword Ranked Search Scheme in Multi-User Settings

With the rapid development of consumer electronics in Industry 5.0, personalized service supplement based on the cloud infrastructure for the Internet of Things (IoT) has been a promising requirement pushed to consumers. During the massive and frequent IoT data interaction from the consumer-centric in Industry 5.0, efficiently searchable encryption for multiple consumers are indispensable. Existing multi-user searchable encryption is based on attribute and predicate encryption technology to realize one-to-many rather than realistic many-to-many scenarios. Moreover, multi-keyword ranked search, dynamic update, and search pattern hiding have not been implemented in the multi-user scenario. In this paper, to address the above problems for consumer electronics in Industry 5.0, we present a privacy-preserving dynamic multi-keyword ranked search scheme over encrypted cloud data to accomplish pay-as-you-consume cloud data security sharing. Our scheme designs a specific tree-based index structure and a “Greedy Breadth-First Search” algorithm to achieve the sub-linear search. To support dynamic updates in the cloud, a novel secure maximum generation protocol is proposed. Finally, the security analysis and experiment evaluation prove our scheme cannot only preserve the privacy of index and search patterns but also support dynamic update operations under the multi-writer/multi-reader setting at an acceptable cost.