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Title

Privacy-Aware an Scalable Content Dissemination in Distributed Social Networks

Document Type

Article

Abstract

Centralized social networking websites raise scalability issues — due to the growing number of participants — and policy concerns — such as control, privacy and ownership of users’ data. Distributed Social Networks aim to solve those by enabling architectures where people own their data and share it whenever and to whomever they wish. However, the privacy and scalability challenges are still to be tackled. Here, we present a privacy-aware extension to Google’s PubSubHubbub protocol, using Semantic Web technologies, solving both the scalability and the privacy issues in Distributed Social Networks. We enhanced the traditional features of PubSubHubbub in order to allow content publishers to decide whom they want to share their information with, using semantic and dynamic group-based definition. We also present the application of this extension to SMOB (our Semantic Microblogging framework). Yet, our proposal is application agnostic, and can be adopted by any system requiring scalable and privacy-aware content broadcasting.

Digital Object Identifier (DOI)

https://doi.org/10.1007/978-3-642-25093-4_11

APA Citation

Kapanipathi, P., Anaya, J., Sheth, A. P., Slatkin, B., & Passant, A. (2011). Privacy-Aware an Scalable Content Dissemination in Distributed Social Networks. Lecture Notes in Computer Science, 7032, 157-172. https://link.springer.com/chapter/10.1007/978-3-642-25093-4_11

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