Research On The Trajectory Privacy Protection Technology Based On K-Anonymous

With the rapid development of mobile networks and location devices,the data in various mobile applications grow into a blowout,causing large data to prevail.At the same time,due to various companies and research institutions of data analysis and mining.Therefore,as long as there is data,there is a data security risks.It is the purpose of this paper to ensure that the trajectory of data is not disclosed.Using the classical trajectory k-anonymous algorithm to publish the trajectory information,the construction of the synchronization trajectory set results in a large loss of information and a low availability of data.At the same time,the classical trajectory anonymous algorithm can not reduce the large error caused by the noise sampling point to the distance measurement when using the Euclidean function to measure the trajectory distance.In this paper,we focus on the trajectory anonymization algorithm to reduce the loss of trajectory equivalence and to avoid noise interference.The main contents of this paper are divided into the following parts:1.The classical algorithm is based on the calculation of the similarity of the trajectory similarity of the Euclidean distance measurement function,which requires time-to-time correspondence and can not measure the similarity between local time migration trajectories.Deleting more location information in the process of constructing trajectory equivalence classes has a greater impact on the availability of trajectory data.In this paper,we propose an DTW-TA anonymity algorithm conbine DTW distance function that can measure the distance of the unequal length with(k,?,p)-anonymous model that a new trajectory anonymity model.To meet the trajectory privacy protection requirements under the premise of effective control of the loss of information.2.In the traditional algorithm to calculate the trajectory distance,due to the presence of noise sampling points,it will lead to a large error in the trajectory distance,reduce the similarity of the trajectory,and reduce the accuracy of the trajectory data.In this paper,an LCSS-TA trajectory anonymity algorithm is proposed based on LCSS distance function and(k,?)-anonymous model.The algorithm reduces the distance error caused by the noise sampling point by mapping the distance between the two sampling points into 0 or 1,and effectively improves the practicability of the trajectory information.In this paper,the DTW-TA trajectory anonymous algorithm based on the DTW distance function is used to improve the usability of the published trajectory data.The LCSS-TA algorithm under the k-anonymous improved model greatly reduces the influence of noise points to trajectory distance metric.The accuracy of the trajectory data is improved.