Research On WEB Application System Privacy Protection In Data Distribution Based On K-anonymous

With the development of Internet technology,web application technologies such as e-commerce and social networking are promoted,and the size of Internet user groups is getting larger and larger.As a result,more and more user data are generated.In the era of big data Privacy protection has become a social and institutional concern for more and more problems.The application of technologies such as data mining makes the issue of privacy disclosure increasingly prominent.Privacy protection is one of the core issues in the research of privacy disclosure control technology in data release.K-Anonymity is the hotspot of privacy protection research in recent years.The research of this paper is based on the intelligent community network service support system developed by our lab,and aims to solve the problem of disclosure of privacy of residents caused by data dissemination of collected community residents' information.Through a lot of research and literature review,I learned about the basic theory of privacy protection and K-anonymity,and three widely used methods to achieve K-anonymity.and further studied the generalized K-anonymity model based on multidimensional attributes.The basic principles and characteristics of this model are analyzed and corresponding improvements are made.In the data preprocessing stage,local abnormal factor detection method is added-LOF algorithm to detect the abnormal points existing in the data set,and to conceal the detected abnormal points,To avoid over-generalization of data caused by abnormal points;In addition,the distribution of the value of quasi-identifier is taken into account in the selection of generalized quasi-identifier property,and approximate analysis is introduced.On this basis,an improved K-anonymity model based on multidimensional attribute generalization is proposed in this paper,and the model is applied to the data anonymity module of the resident information data processing in the Wisdom Network Service Support System.Finally,The improved K-Anonymous model and the wisdom home system health and data anonymity module experiments,the experimental results from the processed data accuracy and algorithm execution time two dimensions to prove the effectiveness of the proposed improvements.