Privacy-preserving analytics for social network data: A survey of currently prevalent tools

Document Type

Book Chapter

Publication Title

Securing Social Networks in Cyberspace

Publisher

Taylor & Francis

School

School of Science / ECU Security Research Institute

RAS ID

40585

Comments

Jindal, R., Falah, A., Anwar, A., & Ahmed, M. (2021). Privacy-Preserving Analytics for Social Network Data: A Survey of Currently Prevalent Tools. In Securing Social Networks in Cyberspace (pp. 17-33). CRC Press.

https://doi.org/10.1201/9781003134527

Abstract

The widespread use and adoption of social media have enabled several improvements in human lives. We now can build and nurture relationships with more people than ever before at a fraction of the cost of previous years. However, with these advancements, social media has also paved the way for privacy concerns like never before; with the growing number of detailed personal profiles online, the need for protecting users' privacy cannot be understated. This chapter aims to provide an accurate landscape of the field of privacy-preserving analytics of social network data. First, the need for privacy-preserving techniques is considered by exploring real-world examples. Next, a popular method of modeling privacy threats for analysis is described, followed by some widely used techniques and tools. Finally, the techniques and tools' relative strengths and capabilities are summarized to paint a complete landscape, and the most pressing directions for future work are discussed. The review of the tools will help to understand the capabilities of the state-of-the-art privacy analysis techniques and their applications.

DOI

10.1201/9781003134527

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