Description

In the Cloud-assisted Internet of Things (IoT), most of the data is sent to the cloud for storage and processing. Data privacy and security are extreme concerns since retrieving data from the cloud will yield privacy disclosure risk due to the cloud’s openness. To this end, this process proposes PERT, a privacy enhanced retrieval Technology for Cloud-assisted IoT. This architecture is designed through an implicit index maintained by edge servers and a hierarchical retrieval model that preserves data privacy by hiding the information of data transmission between the cloud and the edge servers. For the hierarchical retrieval model, we designed a data partition strategy. The edge server stores partial data. In this way, data privacy is preserved since the attacker must get the data maintained by both cloud and edge servers. The detailed performance analysis and extensive experiments have displayed the effectiveness of the technology for data privacy. It is tested that the architecture can efficiently and securely retrieve the stored data while the computation cost is reduced through operation downsizing.