Lightweight Fine – Grained Search Over Encrypted Data in Fog Computing

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Lightweight Fine-Grained Search over Encrypted Data in Fog Computing

Lightweight Fine – Grained Search Over Encrypted Data in Fog Computing

Abstract

Lightweight Fine – Grained Search Over Encrypted Data in Fog Computing,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.

Conclusion

In this Lightweight Fine – Grained Search Over Encrypted Data in Fog Computing paper, we demonstrated a Lightweight Fine-Grained Search (LFGS) system for the resource-limited EUs in fog computing. On the one hand, the basic LFGS system could greatly reduce the computational and storage burden of EUs by outsourcing partial computation and storage to the honest-but-curious FNs without leaking sensitive information; on the other hand, the extended LFGS system could support conjunctive keyword search and attribute update to further narrow down the search scope and avoid unauthorized accesses, respectively. Furthermore, the formal security analysis showed that the LFGS system is selectively secure against CKA and CPA, and the empirical experiments using a real-world data set illustrated the efficiency and feasibility of LFGS system in fog computing.

Asapar to four future work,we will continue to concent rate on expressive search including fuzzy keyword search, semantic keyword search, and so on. Besides, the secure channel utilized in our LFGS system should be eliminated as secure channel will incur high communication burden. Hence, we still need to further improve the efficiency of LFGS system so that it can be applied in various schemes.