Design And Implementation Of Campus Personas System Based On Privacy Protection

With the coming of the era of big data,college students have produced more and more behavioral data in campus network environment,and gradually formed a multi-dimensional data storage system,such as student status information,academic achievement,card consumption,Internet access and so on.This makes it difficult for university administrators to understand the state of students in real time,and can not achieve accurate management of students.How to excavate valuable information in the mass of student data and realize the efficient management of the students has become the first problem to be solved by the management of the University.This paper studies and compares personas at home and abroad,and collects 26 dimensions of campus behavior data,including student status information,card consumption,academic achievement and Internet access.The design is decomposed into three kinds of information,which are basic attributes,statistical attributes and analysis attributes,and a learning based campus user Portrait System Based on privacy protection is designed and realized.According to the analysis needs of campus users,we choose association rules algorithm to mine the correlation between academic courses,and select C4.5 decision tree algorithm to establish the decision model of impoverished students.In order to realize the privacy protection of campus users,we use AES encryption algorithm to encrypt the sensitive fields of users,design and implement the integrity checking of sensitive fields based on XOR correlation.It is verified by experiments that the mining of subject correlation reaches 82%confidence level through Apriori association rules,and the accuracy rate of C4.5 is 87.43%.In the case of privacy protection,the time complexity of the page loading is 2.48s,within the acceptable range of the user.Furthermore,it provides a large data driven decision support for the management of college students.