期刊
IEEE TRANSACTIONS ON SERVICES COMPUTING
卷 12, 期 5, 页码 772-785出版社
IEEE COMPUTER SOC
DOI: 10.1109/TSC.2018.2823309
关键词
Keyword search; Cloud computing; Edge computing; Access control; Encryption; Fog computing; attribute-based encryption; searchable encryption; conjunctive keyword search; attribute update
资金
- National Natural Science Foundation of China [61702404, 61702105, 61672413, 61472310]
- China Postdoctoral Science Foundation [2017M613080]
- Fundamental Research Funds for the Central Universities [JB171504]
- National High Technology Research and Development Program (863 Program) [2015AA016007]
- 111 project [B16037]
- NSFC [U1405255]
- Shaanxi Science & Technology Coordination & Innovation Project [2016TZC-G-6-3]
Fog computing, as an extension of cloud computing, outsources the encrypted sensitive data to multiple fog nodes on the edge of Internet of Things (IoT) to decrease latency and network congestion. However, the existing ciphertext retrieval schemes rarely focus on the fog computing environment and most of them still impose high computational and storage overhead on resource-limited end users. In this paper, we first present a Lightweight Fine-Grained ciphertexts Search (LFGS) system in fog computing by extending Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Searchable Encryption (SE) technologies, which can achieve fine-grained access control and keyword search simultaneously. The LFGS can shift partial computational and storage overhead from end users to chosen fog nodes. Furthermore, the basic LFGS system is improved to support conjunctive keyword search and attribute update to avoid returning irrelevant search results and illegal accesses. The formal security analysis shows that the LFGS system can resist Chosen-Keyword Attack (CKA) and Chosen-Plaintext Attack (CPA), and the simulation using a real-world dataset demonstrates that the LFGS system is efficient and feasible in practice.
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