Nudging Nemo: Helping Users Control Linkability Across Social Networks

  • Rishabh Kaushal
  • Srishti Chandok
  • Paridhi Jain
  • Prateek Dewan
  • Nalin Gupta
  • Ponnurangam Kumaraguru
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10540)

Abstract

The last decade has witnessed a boom in social networking platforms; each new platform is unique in its own ways, and offers a different set of features and services. In order to avail these services, users end up creating multiple virtual identities across these platforms. Researchers have proposed numerous techniques to resolve multiple such identities of a user across different platforms. However, the ability to link different identities poses a threat to the users’ privacy; users may or may not want their identities to be linkable across networks. In this paper, we propose Nudging Nemo, a framework which assists users to control the linkability of their identities across multiple platforms. We model the notion of linkability as the probability of an adversary (who is part of the user’s network) being able to link two profiles across different platforms, to the same real user. Nudging Nemo has two components; a linkability calculator which uses state-of-the-art identity resolution techniques to compute a normalized linkability measure for each pair of social network platforms used by a user, and a soft paternalistic nudge, which alerts the user if any of their activity violates their preferred linkability. We evaluate the effectiveness of the nudge by conducting a controlled user study on privacy conscious users who maintain their accounts on Facebook, Twitter, and Instagram. Outcomes of user study confirmed that the proposed framework helped most of the participants to take informed decisions, thereby preventing inadvertent exposure of their personal information across social network services.

Keywords

Privacy leakage Identity resolution Online social media 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Rishabh Kaushal
    • 1
  • Srishti Chandok
    • 1
  • Paridhi Jain
    • 2
  • Prateek Dewan
    • 1
  • Nalin Gupta
    • 1
  • Ponnurangam Kumaraguru
    • 1
  1. 1.Indraprastha Institute of Information TechnologyDelhiIndia
  2. 2.American Express, Big Data LabsBangaloreIndia

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