In recent years, ridesharing has been widely adopted as an instance of sharing economy. When using ridesharing service, users (i.e., drivers and riders) have to share their private trip information with the service provider, which causes great privacy risks to them. In order to protect user’s privacy, based on private set intersection cardinality (short for PSI-CA), we propose a privacy-preserving and efficient ridesharing scheme (short for PSI-PPER). It enables the service provider to efficiently match riders with appropriate drivers without learning their private trip information. In PSI-PPER, we adopt ‘‘screen and then match” method, which means the service provider first screens each rider’s possible matching drivers, and then performs matching operations on each rider and its possible matching drivers. For matching riders and drivers efficiently, the secure ride-matching computation is converted into private set intersection cardinality and is achieved by a one-party to multi-party PSI-CA protocol, which is designed based on vector oblivious linear evaluation and oblivious key-value stores. We prove the security of the proposed scheme theoretically and evaluate its performance through experiments. The results show that the proposed scheme can achieve practical ride-matching accuracy. In addition, PSI-PPER provides higher security and superior efficiency compared to other secure ride-matching schemes with large number of drivers and large trip length.

Online ride-hailing and navigation (ORHN) is a significant application in location-based services (LBSs). With this application, users can get convenient services in daily travel. However, during the process of ORHN, the user has to confront the violation of personal privacy (such as the initial point, the destination, and the moving path) from the taxi driver or the ride-hailing sharer. Therefore, in order to cope with the problem of privacy violation, in this article, an initial, route, and destination preservation ride system (short for IRDP Ride system) is proposed. In the IRDP Ride system, the initial point, the destination, and the route can be preserved during the process of ORHN, no matter whether the adversary (such as the un-trusted driver or sharer) utilizes the analysis method in the same car (such as the range attack or the segment direction attack). In this article, before elaborating on the IRDP Ride system, two types of methods used for analyzing the initial point and destination were given. Then based on the characteristics of Voronoi and the navigation deviation, three algorithms used in this system for providing privacy preservation service are proposed. In the last part of this article, the IRDP Ride system’s security and stability are discussed from the theoretical analysis. At the same time, this system is also verified with several groups of experiments in the real environment to determine the optimization parameters, and then this system is also compared with other similar systems to demonstrate its superiority.

Nowadays, blockchain technology and industry has developed rapidly all over the world, which is inseparable from continuous innovation and improvement on smart contract technology. Therefore, by summarizing the working principle and application research status of blockchain smart contract, this paper analyzes the development and challenges of smart contract. Firstly, we introduce the model and operation principle of blockchain smart contract for the overall architecture, analyze the deployment process of smart contract with Ethereum, Hyperledger Fabric and EOSIO, and make a comparative analysis from the technical level. And taking Byteball, InterValue and IOTA platforms as examples, we introduce the deployment process and application potential for DAG-based blockchain smart contract. Additionally, we also summarize the application research of smart contract for international and Blockchain Oracle, and discuss its innovative application and development trend in the future. Secondly, we introduce the application status of smart contract with Ethereum and Hyperledger Fabric platforms from the aspects of financial transactions, Internet of things, medical applications, and supply chain, and further discuss EOS (enterprise operation system), Blockchain Oracle and other application fields. Furthermore, we introduce the application advantages and challenges to smart contract for industrial Internet from the fields of manufacturing, food industry, industrial Internet of things and industry 4.0. Finally, we discuss the challenges faced by smart contract with technical issues, analyzes the impact on large-scale applications and mining system on the sustainable development of smart contract, and looks forward to the future research direction of blockchain smart contract.

The centralized and distributed models are the main system architecture of privacy protection in location-based services (LBS). In the model of centralized, the trusted third party (TTP) is used to provide location privacy, but it is usually thought as the point of attack and the bottleneck of service, which makes the distributed model attract more attention. However, although a large number of algorithms were proposed under this model, they were mainly focussed on the protection of the snapshot query and difficult to provide privacy in the continuous query. Especially that, with the difference of anonymous users, the adversary can get rid of the anonymous users and identify the issuer, and then the privacy of the issuer will be revealed. In order to deal with this problem, we propose an uncertain continuous collaborative users finding algorithm (UCCUFA), which utilizes the uncertainty cells of region grid and the collaborative users to provide query results to make the issuer hiding behind the collaborative users. In this algorithm, all query results are provided by collaborative users, and no information interacted between the issuer and the LBS server during the procedure of continuous query. At last, we utilize the security analysis and experimental results further verify the effectiveness of location privacy protection and the performance efficiency of our proposed algorithm.

In location based services (LBSs) of snapshot query, both of query and location privacy should be preserved. Most preceding schemes usually employed a trusted third party (TTP) to achieve k-anonymity, and perturb the real query and location with other k-1 users, but this scheme may be influenced by the single point failure and performance bottleneck. In order to solve this problem, another scheme to achieve k-anonymity with collaborative users through short-range communication was proposed. After deeply analyzing the inherent drawbacks of existing schemes of this type, we have found that most of them mainly focus the location privacy and usually neglect the correlation between query and location. In order to preserve the query privacy, based on the user collaborative scheme, we propose a scheme with query information divide and exchange with random users (short for QDER). This scheme can provide preserving service for both query and location privacy simultaneously. Then we analyze the attack from passive and active adversaries and use entropy to measure the privacy level. Finally, security analysis and experimental evaluations further verify the effectiveness and efficiency.