An Intelligent Detection Method of Personal Privacy Disclosure for Social Networks | Zendy

Haiyan Kang | Zendy; Yanhang Xiao | Zendy; Jie Yin | Zendy

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An Intelligent Detection Method of Personal Privacy Disclosure for Social Networks

Author(s) -

Haiyan Kang,

Yanhang Xiao,

Jie Yin

Publication year - 2021

Publication title -

security and communication networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.446

H-Index - 43

eISSN - 1939-0114

pISSN - 1939-0122

DOI - 10.1155/2021/5518220

Subject(s) - computer science , personally identifiable information , construct (python library) , computer security , support vector machine , privacy protection , internet privacy , social network (sociolinguistics) , data mining , social media , artificial intelligence , world wide web , computer network

With the increase of the number of users in the current social network platform (taking WeChat as an example), personal privacy security issues are important. This paper proposes an intelligent detection method for personal privacy disclosure in social networks. Firstly, we propose and construct the eigenvalue in social platform. Secondly, by calculating the value of user account assets, we can obtain the eigenvalue to calculate the possibility of threat occurrence and the impact of threat. Thirdly, we analyse the situation that the user may leak the privacy information and make a score. Finally, SVM algorithm is used to classify the results, and some suggestions for warning and modification are put forward. Experiments show that this intelligent detection method can effectively analyse the privacy leakage of individual users.

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