Practical Byzantine fault tolerance (PBFT) is one of the most popular consensus protocols of the blockchain. However, in the PBFT, the enthusiasm of reliable nodes cannot be stimulated effectively, and a large amount of communication resources are used for data consistency. Therefore, a new consensus protocol-credit-delegated Byzantine fault tolerance (CDBFT)-is proposed in this paper. The CDBFT works as the following: 1) a voting rewards and punishments scheme and its corresponding credit evaluation scheme are proposed not only to stimulate enthusiasm of reliable nodes but also to reduce the participation of abnormal nodes in the consensus process, and the virtuous circle of the system can be founded and 2) consistency and checkpoint protocols based on PBFT are proposed to improve the efficiency and flexibility of system. From the simulation results, a conclusion can be drawn, the participation probability of abnormal nodes in the consensus process can be reduced to 5%, and the efficiency and stability of the system are improved greatly in the long-time running.

Most of the mobile phones have GPS sensors which make location based service (LBS) applicable. LBS brings not only convenience but also location privacy leak to us. Achieving anonymity and sending private queries are two main privacy-preserving courses in LBS. A novel location privacy-preserving method is proposed based on Voronoi graph partition on road networks. Firstly, based on the prediction of a user's moving direction, a cooperative -anonymity method is proposed without constructing cloaking regions which may lead to efficiency decline in continuous query. And then, a query algorithm is proposed without providing any user's actual location, replaced by continuous anchor sequence, to LBS provider. This algorithm can work out precise results according to candidate sets returned by LBS provider and it also solves uneven distribution problem in SpaceTwist. Performance analysis and experiments show that our method achieves a preferable tradeoff between QoS and location privacy preserving; it has obvious advantages compared with other methods.

A user's staying points in her trajectory have semantic association with privacy, such as she stays at a hospital. Staying at a sensitive place, a user may have privacy exposure risks when she gets location based service (LBS). Constructing cloaking regions and using fake locations are common methods. But if regions and fake positions are still in the sensitive area, it is vulnerable to lead location privacy exposure. We propose an anchor generating method based on sensitive places diversity. According to the visiting number and peak time of users, sensitive places are chosen to form a diversity zone, its centroid is taken as the anchor location which increases a user's location diversity. Based on the anchor, a query algorithm for places of interest (POIs) is proposed, and precise results can be deduced with the anchor instead of sending users' actual location to LBS server. The experiments show that our method achieves a tradeoff between QoS and privacy preserving, and it has a good working performance.

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Abstract. In the big data protecting technologies, most of the existing data protections adopt entire encryption that leads to the researches of lightweight encryption algorithms, without considering from the protected data itself. In our previous paper (FGEM), it finds that not all the parts of a data need protections, the entire data protection can be supplanted as long as the critical parts of the structured data are protected. Reducing unnecessary encryption makes great sense for raising efficiency in big data processing. In this paper, the improvement of FGEM makes it suitable to protect semi-structured and unstructured data efficiently. By storing semi-structured and unstructured datum in an improved tree structure, the improved FGEM for the datum is achieved by getting congener nodes. The experiments show the improved FGEM has short operating time and low memory consumption.