Research On LBS Anonymous Region Optimization Algorithm And Privacy Measurement Method Based On Internet Of Things

In recent years, with the development of the Internet of Things(Io T) industry, the location-based services(LBS) have also rapidly developed. Users are enjoying more and more convenient services; meanwhile, they also begin to pay more attention to their own privacy protection. Due to the complexity of environment, LBS privacy protection in the environment of Io T is more important. The research of LBS privacy protection mainly focuses on anonymous region construction algorithm and accuracy of query result. There still exists a contradiction that cannot be effectively balanced between the effect of privacy protection and accuracy of processing results. In view of the above contradiction, in this paper, the LBS anonymous region optimal selection algorithm and privacy measurement method under the environment of Io T is analyzed. In the condition of ensuring the reliability of the anonymous device itself, a safe and efficient anonymous region construction algorithm and its corresponding privacy evaluation method are implemented. The specific research contents are as follows:1. For security problem of LBS model in the environment of Io T, a LBS Privacy Protection Model Based on Expanded Anonymous Server is put forward. The safety of the anonymous system is analyzed in this model and it is extended itself based on its original structure to ensure its own security. Therefore, based on the secure anonymous server, the LBS privacy security model can be constructed. Analysis shows that the model can effectively protect the privacy and security of the users’ identity, location and service contents.2. In view of the contradiction between the effect of privacy protection and the accuracy of processing results, a construction method based on boundary of anonymous region is proposed. According to the anonymous parameter K, the algorithm firstly determined the number of users within the anonymous region, and then connected the consumers in the outermost. Thus, a closed convex polygon is constituted. In the end, anonymous region area is calculated and it is compared with minimum anonymous area that users required. And it is sent to LBS servers. Experimental results show that the proposed algorithm can effectively reduce the anonymous area and improve the accuracy of the query results.3. Based on the anonymous area construction algorithm proposed in this paper, a privacy evaluation method based on entropy is proposed. The proposed algorithm quantified the level of user’s uncertainty in the anonymous area and achieved the requirement of the quantification of the degree of privacy. At the same time, it utilizes the indicators to effectively measure the contradiction between the accuracy of query results and the effectiveness of privacy protection.The LBS privacy protection model based on Io T is preliminarily researched in this paper, and the limitation of the actual mobile communication terminal is taken into consideration. Many problems are needed to be future researched and settled when the model is applied in the real mobile speech communication.