In order to solve the problem of out-off-balance caused by accuracy of location information between privacy protection security and query service quality, considering basic information comprehensively such as the environment and geographical features and so on, and adopting k- anonymous privacy protection mechanism, we present a k-anonymous location privacy protection method of polygon based on density distribution. Firstly, a k-anonymous irregular polygon region is structured in whole area. Then, according to the preset anonymous region and density threshold, the better effects of anonymous are obtained by expanding the region or adding the random dummy locations. Experimental results show that the proposed method improves the efficiency of anonymous and query accuracy. The balance between privacy protection security and query quality is achieved.
With the increase of per capita car ownership, traffic accidents frequently occur, in which rear-end collision accounts for 30% to 40% of the total accidents; thus, rear-end collision has become the primary factor of traffic environment deterioration. Therefore, how to improve road traffic safety and reduce the probability of rear-end collision has become a major social concern. In this study, based on the safety pre-warning algorithm, a vehicle collision model was built, and a vehicle anti-collision warning system was established. The calculation was performed based on the sample data to obtain the prediction value of vehicle collision time under different driving speeds, so as to provide drivers with effective response time and reduce the casualties and property losses caused by a vehicle collision. The experimental results showed that the accuracy rate of the pre-warning reached 80% when the speed was regarded as a variable, and the simulation results showed that the early pre-warning or delayed pre-warning rate was very low, and the timeliness rate reached 89%, which enables drivers to react quickly in the appropriate time and effectively reduces the risk of vehicle rear-end collision.
The dynamic change of vertex degree in a dynamic social network will lead to vertex identity disclosure given the deficiencies in current privacy protection methods, such as the destruction of community structure and low data processing capability of a single workstation. The dynamic social network degree sequence anonymity (DSNDSA) method to protect community structure is proposed. The method obtains the grouping and anonymous results based on a compressed binary tree constructed by a new method called a multidimensional vector. Dummy vertices are added in parallel to construct anonymous graphs. Distributed to merge dummy vertices method based on the community is designed to reduce the number of vertices added to satisfy the anonymity model. A divide and the agglomerate algorithm is expanded for community detection. The experimental results show that the proposed algorithm based on GraphX can overcome the defects of the traditional algorithm in community protection while meeting the requirement of anonymity.
This paper proposes a dummy k-anonymous location privacy protection based on a fast-matching method that adopts the space coordinate transformation algorithm. First, the 2-D coordinates are converted to binary Morton code. With the fast matching method, non-adjacent position points distributed in different grids are selected as candidate sets of dummy positions. Then, the semantic similarity of place name information of position points in the candidate sets is calculated using the edit distance, and k-1 position points with the smallest semantic similarity are selected as dummy positions. While satisfying the semantic l-diversity and physical dispersion, this method can improve the generation efficiency of dummy locations and further improve the quality of location service.
