With the enhancement of the positioning function of mobile devices and the upgrade of communication networks, location-based service (LBS) has become an important application of mobile devices. Among the numerous researches on location privacy preservation, cloud-based location privacy preservation has become a hot topic, but it undoubtedly brings new problems such as data confidentiality and user privacy disclosure. This paper proposes an accountable outsourced LBS privacy-preserving scheme. In the outsourcing scenario, in order to make users interact with cloud server to obtain query data, firstly we construct location hierarchical index and attribute hierarchical index based on Bloom Filter, and secondly we divide one region into atomic regions using Hilbert Curve, both of which ensure the privacy of query and improve the efficiency of query. At last, we realize the sharing of encrypted data among different users by accountable proxy re-encryption (APRE) technology, which can effectively suppress the abuse of proxy re-encryption key. We demonstrate the correctness of the proposed scheme through security analysis, and show the effectiveness of the scheme through performance analysis.
Compared with traditional voting methods, electronic voting can effectively avoid the phenomenon of fraud for personal gains in various links, it is faster and more accurate in the tallying stage. However, many electronic voting systems have many problems such as inability to verify ballots, easy to be forged, and low computing efficiency. We propose an electronic voting protocol based on homomorphic signcryption and blockchain.The protocol makes the voting process public through blockchain and replaces the traditional trusted third party with the smart contract. It uses the homomorphic encryption algorithm and the homomorphic signcryption algorithm to encrypt and sign the ballot and uses their aggregation properties to perform homomorphic tally on the encrypted votes. This not only reduces the excessive burden on the voters but also improves the voting efficiency. At the same time, it can satisfy the security of electronic voting, and the amount of calculation is small, so it is more convenient and flexible to use in large-scale voting.
With the maturity of Internet of Things technology, location-based service (LBS) is developing rapidly in intelligent terminal devices, and it brings new vitality to the fields of logistics, transportation, product traceability and so on. The popularity of LBS produces a lot of spatial data, which inevitably brings burden to the storage and management of LBS provider (LBSP). With the help of cloud computing and cloud storage, outsourcing spatial data to cloud server has become a new trend. However, due to the cloud server is not trusted, data outsourcing will face the problems of data disclosure and query disclosure. Range query is a common query in LBS, considering the situation of data outsourcing, this paper proposes an accurate range query (ARQ) scheme, which can realize efficient range query while preserving LBSP's data privacy and user's query privacy from being disclosed to the cloud server. The ARQ scheme issuitable for spatial data in any form without being limited to the case that the data points are only integers, which has a certain practical significance. In addition, by dividing the region into atomic regions, ARQ can realize sub-linear search time and ensure dynamic update of spatial data. We proved the security of the proposed scheme through security analysis, and demonstrated the effectiveness of the scheme through experiments.
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