Privacy-aware searching with oblivious term matching for cloud storage
The Journal of Supercomputing
Efficient keyword search over encrypted data with fine-grained access control in hybrid cloud
NSS'12 Proceedings of the 6th international conference on Network and System Security
Journal of Computer and System Sciences
Compromising privacy in precise query protocols
Proceedings of the 16th International Conference on Extending Database Technology
Controllable privacy preserving search based on symmetric predicate encryption in cloud storage
Future Generation Computer Systems
Supporting complex queries and access policies for multi-user encrypted databases
Proceedings of the 2013 ACM workshop on Cloud computing security workshop
Privacy-preserving data utilization in hybrid clouds
Future Generation Computer Systems
Dividing secrets to secure data outsourcing
Information Sciences: an International Journal
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In cloud computing, clients usually outsource their data to the cloud storage servers to reduce the management costs. While those data may contain sensitive personal information, the cloud servers cannot be fully trusted in protecting them. Encryption is a promising way to protect the confidentiality of the outsourced data, but it also introduces much difficulty to performing effective searches over encrypted information. Most existing works do not support efficient searches with complex query conditions, and care needs to be taken when using them because of the potential privacy leakages about the data owners to the data users or the cloud server. In this paper, using on line Personal Health Record (PHR) as a case study, we first show the necessity of search capability authorization that reduces the privacy exposure resulting from the search results, and establish a scalable framework for Authorized Private Keyword Search (APKS) over encrypted cloud data. We then propose two novel solutions for APKS based on a recent cryptographic primitive, Hierarchical Predicate Encryption (HPE). Our solutions enable efficient multi-dimensional keyword searches with range query, allow delegation and revocation of search capabilities. Moreover, we enhance the query privacy which hides users' query keywords against the server. We implement our scheme on a modern workstation, and experimental results demonstrate its suitability for practical usage.