Toward a User-Centric Differential Privacy Service for Online Social Networks

In the era of pervasive online social networks (OSNs), the erosion of information privacy is occurring at an unprecedented rate. Empowering individuals with user-centric control over their private information is crucial to fostering public confidence in OSN services. Hence, the investigation into the personalized privacy configurations within the framework of differential privacy for OSNs, particularly for social relationships, is captivating. In this paper, we introduce a Collaborative Personalized Edge Differential Privacy model (CPEDP), ensuring personalized protection for sensitive social relationships while retaining the high utility of network features. Specifically, CPEDP allows each user to define a policy specification consisting of two complementary components: secret specifications at the edge level to identify sensitive relationships, and privacy specifications at the user level to determine personalized privacy parameters. These user-defined preferences are integrated through a collaborative privacy decision-making process that ensures consistent and interpretable privacy guarantees. Furthermore, we formalize the privacy primitive of CPEDP and develop a sampling-based mechanism to effectively implement the proposed model. Finally, comparative experiments on real-world datasets confirm that CPEDP achieves superior privacy-utility trade-offs, yielding more accurate estimates of key graph statistics through policy-driven personalization.