Privacy Protection of Social Networks Based on Classified Attribute Encryption

With the rapid development of social networks, privacy has also attracted attention. Based on this problem, a privacy protection scheme for social networks based on classified attribute encryption (PPSSN) is proposed for the data owner and attribute management server to manage user permissions; the approach reduces data owner overhead and also avoids use of a property management server to limit access user collusion attacks. To balance the privacy and security of data publication, this scheme classifies users and designs access control for different users and different privileges. In addition, this paper also introduces a good friend data cache mechanism to improve and optimize the original scheme to reduce the cost of decryption. The efficiency and system overhead of the proposed scheme are compared and analyzed based on experiments. The experiments show that the proposed scheme improves query efficiency, reduces system cost, and enhances privacy security.