Parallel clustering-based k-anonymity algorithm in Internet of things
Wei Huo-wan · Information technology newsletter · 2013
Two parameters about tolerable space granularity and tolerable time granularity in the Internet of things( IOT) are given and a k-anonymity model for IOT environment is created. A concept of the distribution sequence of data sets is proposed to optimize the generated cluster seeds. The data are clustered in parallel such that the data for multiple nodes are contained in the equivalence class,the data with specific location information will be divided into different equivalence classes to fuzzy their specific location information,the label layout characteristics is eliminated,and a k-anonymity algorithm for privacy protection in Internet of things is designed. The experimental results show that the presented algorithm can effectively protect the privacy of data and improve data security in premise of ensuring data availability in Internet of things.