Privacy preservation based on rotation perturbation in weighted social networks

With the development of social networks, users' privacy is threatened seriously. To protect privacy, in this paper a rotation perturbation method based on algorithm RBT (Rotation-Based Transformation) is improved. The new algorithm PPRRP (Privacy Preservation by Random Rotation Perturbation) establishes social networks into a vectors model and carries on rotation perturbation. This method reduces the amount of computation and improves the rotation perturbation efficiency. The random function generating the rotation matrix mentioned in this paper can resist the recognition attack. Simulation experiments prove PPRRP has a better performance.

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