Abstract: Aiming at the problems of excessive noise addition and unbalanced privacy protection in the differential privacy protection algorithm of weighted social networks, a privacy protection algorithm combining spectral clustering algorithm and differential privacy protection model is proposed. Firstly, to solve the problem of excessive noise addition caused by the way of directly adding noise to the side weights of social networks by traditional differential privacy protection algorithms, combined with the spectral clustering algorithm, the weighted social networks are clustered into different clusters, and different clusters are randomly selected. The method of adding noise reduces the amount of noise added and improves the availability of data. Secondly, new privacy budget parameters are designed, and the amount of noise added is determined according to the weight of the social network side, so as to achieve a more balanced privacy protection. Finally, theoretical derivation and experiments prove that the data processed by the proposed algorithm have higher availability.

Key words: weighted social network, differential privacy, spectral clustering