Researching Of Method For Anonymous Issuing Technology Of Wearable Devices Data

With development of IoT and micro-electronic technology,wearable device is becoming popular.But the popularity of wearable device brings convenient life style and privacy problem at the same time.The data collected from wearable devices contains users' privacy.But data publishing could bring some benefits to users and data holders.How do we publish data in a privacy preserved way is valuable to do deep research.Anonymous publishing is an important method to preserve privacy.Data could be published in a wide range,all the people could acquire the data.The usability of data could be well preserved,because there is no change in the sensitive data.Present anonymous publishing methods are not secure enough to preserve the users' privacy because the wearable device data could be used to recognize the identity information.The analyzer could de-anonymous the data even though the data conform the principle of these anonymous method.On the other hand,the static publishing is not enough to fit the development of wearable device.However,data republishing is also an important reason to cause privacy leakage.According to the current situation of wearable device and problems mentioned above,to well address the privacy problem of wearable devices,this paper brings three contributions:(1)This paper illustrates the details about the privacy leakage process of wearable devices.The most important thing of privacy preserving is getting know how the privacy to be leaked.Understanding the data analysis method is important to preserve privacy.(2)This paper proposes Similarity based Partition K-anonymity after we getting know the privacy leakage approach.This method promotes the security of wearable devices data.In the end,we demonstrate the performance of our method by a well–designed experiment.(3)Data republication is an important approach to leak privacy.Comparing different versions of data could lead privacy leakage.This paper proposes Clustering based Republication method to keep privacy contained in data when we republish data.This method could cause low information loss bring high performance to us at the same time.