Privacy-preserving Data Dissemination Scheme Based on Searchable Encryption, Publish–subscribe Model, and Edge Computing

Attribute-based Searchable Encryption is emerging as a promising cryptographic technique supporting data protection, flexible access control, and keyword search over encrypted data. The current scientific literature already investigated its adoption in cloud-based services and additionally explored the usage of edge computing to implement some of the cryptographic tasks in scenarios with limited computational capabilities (such as Internet of Things). In the majority of the available solutions, however, the remote cloud is still responsible for data storage, keyword search over encrypted data, and delivery tasks. Indeed, the heavy computational load generated in scenarios with multiple data producers and data consumers (never studied yet) and large communication latencies can inevitably compromise the overall system performance. To bridge this gap, this work proposes a decentralized service architecture offering privacy-preserving data dissemination, by jointly leveraging attribute-based Searchable Encryption techniques, publish–subscribe communication model, and edge computing capabilities. Here, customized Edge Servers are deployed at the network edge to (i) collect subscription requests encoded via Searchable Encryption Trapdoors, (ii) receive data publications, encrypted via Attribute-based Searchable Encryption scheme, (iii) implement keyword search over encrypted data, and (iv) deliver encrypted data only to authorized requesters. Experimental tests explored the impact of network configuration and traffic load on both communication latency and energy consumption. Obtained results demonstrated the unique ability of the proposed solution to achieve shorter data delivery delays as well as less energy consumption with respect to cloud-based alternatives.