【摘要】 用户的定位信息所带来的隐私泄漏已经严重制约普适应用的发展。在已有的定位模糊保护算法中,具体代表性的是AICA,在分析AICA的缺点的基础上,提出了一种新的定位隐私保护算法——DBSCA Density-Based Spatial Cloaking Algorithm。DBSCA通过对普适空间中的网格化转换,巧妙地将最优模糊空间问题转化为最大密度空间问题,通过用户邻近分布矩阵和用户相对密度实现了用户最优模糊空间的寻找。仿真实验表明:DBSCA算法在平衡用户匿名需求和LBS服务准确性需求上优于AICA算法,且具有较好稳定性能更好地适用于频繁变化的普适环境。更多还原

【Abstract】 The privacy leakage caused by location information seriously restricts the development of pervasive applications.AICA is a known spatial fuzzy algorithm for location protection.Based on the analysis of the shortcoming of AICA,a new privacy protect algorithm is proposed in the paper,which is named Density-Based Spatial Cloaking Algorithm(DBSCA).DBSCA subtly transforms the optimal obfuscating region problem into the maximum density re-gion problem by grid processing of pervasive space.In DBSCA,the Optimized Cloaking Region(OCR) is generated with distribution matrix and relative density matrix of neighboring users.The extensive simulations show that,DBSCA algorithm has the advantage to AICA algorithm with the balance of K-anonymous and accuracy of Location Based Services(LBS),it is specially suitable for frequently changes of pervasive environment because of its better stability.更多还原