PRINCE: Privacy-Preserving Mechanisms for Influence Diffusion in Online Social Networks

TL;DR

PRINCE introduces the first differentially private mechanism to address privacy and incentive issues in influence diffusion within online social networks, combining theoretical properties with extensive performance evaluation.

Contribution

It proposes a novel privacy-preserving influence diffusion mechanism using differential privacy, filling a key gap in existing social network influence models.

Findings

PRINCE achieves good performance in experiments.

It maintains strong privacy guarantees.

It is the first to apply differential privacy to influence diffusion.

Abstract

This paper has been withdrawn by the author due to a crucial sign error in equation 1. With the advance of online social networks, there has been extensive research on how to spread influence in online social networks, and many algorithms and models have been proposed. However, many fundamental problems have also been overlooked. Among those, the most important problems are the incentive aspect and the privacy aspect (eg, nodes' relationships) of the influence propagation in online social networks. Bearing these defects in mind, and incorporating the powerful tool from differential privacy, we propose PRINCE, which is a series of \underline{PR}ivacy preserving mechanisms for \underline{IN}fluen\underline{CE} diffusion in online social networks to solve the problems. We not only theoretically prove many elegant properties of PRINCE, but also implement PRINCE to evaluate its performance extensively. The evaluation results show that PRINCE achieves good performances. To the best of our knowledge, PRINCE is the first differentially private mechanism for influence diffusion in online social networks.