Research On Multi-level Security Scheme Of Social Network User Information

With the development and popularization of network technology and smart devices,social networking sites are used by more and more people.Before using the social network,users need to register in the social network,fill in and submit user information.User information involves p ersonal privacy.When users use social networks,how to protect the privacy and security of user information has become a highly concerned issue for users.Encryption of user information is one of the privacy and security methods to protect user informatio n.If high-security encryption algorithm is used to encrypt and decrypt all user information,the security of user information is effectively protected.However,the use of high-security encryption algorithm to encrypt and decrypt massive user information requires a large amount of computing and storage resources,resulting in the decline of the service quality of social networks.Therefore,this paper studies the privacy risk classification and multilevel encryption of social network user information.The main research work is as follows:Firstly,this paper gives an overview of social networks,analyzes the security features and security strategies of social networks in detail,and introduces the fuzzy c-means clustering algorithm and encryption algorithm.Then,the classification of privacy risks of social network users' information is the premise and basis for the realization of multi-level encryption of user information.Therefore,this paper proposes a privacy risk classification model of social network users' information,which determines the privacy risk level of user information according to the sensitivity and visibility of user information.The sensitivity of user information was calculated according to the project response matrix that users set the level of information privacy,and the visibility of user information was calculated according to the accessibility,extraction difficulty,reliability and user privacy awareness of user information.An improved fuzzy c-means clustering algorithm was used to calculate the visibility of user information.The proposed model is validated through experiments,which show that the proposed model can effectively classify the privacy risks of social network users' information.Finally,this paper puts forward a kind of social network users' information classification HEUI encryption scheme,according to user information privacy risk level,risk grade of different privacy of user information encryption algorithm USES different security strength,the low risk of priva cy of user information using DES encryption algorithm,the secondary user information pri vacy risks,encrypted using AES-256 algorithm for high privacy risks of user in formation encrypted using AES-256 algorithm.HEUI was tested under Pycharm 2018.3 enviro nment,and the experimental results were analyzed from the aspects of data encryption time and data throughput,etc.The experimental results showed that HEUI could not only effectively protect the privacy and security of user information,but also could n ot lead to a serious decline in the service performance of social network.