Fractal Intelligent Privacy Protection in Online Social Network Using Attribute-Based Encryption Schemes

While the online social network (OSN) has brought much convenience to users, there are still some serious problems, such as personal privacy leaks. Today, OSN security and privacy protection are one of the most important focuses of the research. In this paper, we present an intelligent privacy protection approach to solve problems of security and privacy protection in OSNs. First, the proposed algorithm combines a neural network with a hybrid hierarchy genetic algorithm and radial basis function, which is used to construct a prediction model of OSN security. Then, a support vector machine is applied to preprocess information of the OSN, and the attribute-based encryption scheme is adopted to encrypt the OSN information. Finally, a particle swarm optimization algorithm is used to improve OSN security and privacy protection. The experimental results demonstrate the effectiveness of the proposed method.

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