Currently, searchable encryption has attracted considerable attention in the field of cloud computing. The existing research mainly focuses on keyword-based search schemes, most of which support the exact matching of keywords. However, keyword-based search schemes ignore spelling errors and semantic expansions of keywords. The significant drawback makes the existing techniques unsuitable in cloud computing as it greatly affects system usability and can not completely satisfy the users' search intentions. In this paper, we propose an effective fuzzy semantic searchable encryption scheme (FSSE) that supports multi-keyword search over encrypted data in cloud computing. In our scheme, we exploit a keyword fingerprint generation algorithm to generate a fingerprint set of the keyword dictionary and a fingerprint of the query keywords, and employ Hamming distance to quantify keywords similarity. Based on the proposed fingerprint generation algorithm and Hamming distance, we realize fuzzy search. Furthermore, we utilize the semantic expansion technique to expand query keywords and calculate the semantic similarity between the query keywords and the expanded word of the query keywords to achieve the semantic search. To improve the search efficiency, we construct an inverted index structure and use the vector intersection matching as well as short-circuit matching operations to effectively filter irrelevant documents. The theoretical analysis and experimental results demonstrate that our proposed scheme satisfies the security guarantee of searchable encryption, enhances system usability, and is more efficient in comparison with the state of the art schemes. INDEX TERMS Searchable encryption, cloud computing, fuzzy semantic search, multi-keyword search. I. INTRODUCTION
Data aggregation is an important method to reduce the energy consumption in wireless sensor networks (WSNs); however, it suffers from the security problems of data privacy and integrity. Existing solutions either have large communication and computation overheads or only produce inaccurate results. This paper proposes a novel secure data aggregation scheme based on homomorphic primitives in WSNs (abbreviated as SDA-HP). The scheme adopts a symmetric-key homomorphic encryption to protect data privacy and combines it with homomorphic MAC synchronically to check the aggregation data integrity. It compares the scheme with the previously known methods such as SIES, iPDA, and iCPDA in terms of the data privacy protection efficiency, integrity performance, computation overhead, communication overhead, and data aggregation accuracy. Simulation results and performance analysis show that our SDA-HP requires less communication and computation overheads than previously known methods and can effectively preserve data privacy, check data integrity, and achieve high data transmission efficiency and accurate data aggregation rate while consuming less energy to prolong network lifetime. To the best of our knowledge, this is the first work that provides both integrity and privacy based on homomorphic primitives.
Data aggregation is an important technique for reducing the energy consumption of sensor nodes in wireless sensor networks (WSNs). However, compromised aggregators may forge false values as the aggregated results of their child nodes in order to conduct stealthy attacks or steal other nodes' privacy. This paper proposes a Secure-Enhanced Data Aggregation based on Elliptic Curve Cryptography (SEDA-ECC). The design of SEDA-ECC is based on the principles of privacy homomorphic encryption (PH) and divide-and-conquer. An aggregation tree disjoint method is first adopted to divide the tree into three subtrees of similar sizes, and a PH-based aggregation is performed in each subtree to generate an aggregated subtree result. Then the forged result can be identified by the base station (BS) by comparing the aggregated count value. Finally, the aggregated result can be calculated by the BS according to the remaining results that have not been forged. Extensive analysis and simulations show that SEDA-ECC can achieve the highest security level on the aggregated result with appropriate energy consumption compared with other asymmetric schemes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.