research-article

Aegis: An Agent for Multi-party Privacy Preservation

Authors:

Hicham HageAuthors Info & Claims

AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Pages 68 - 77

https://doi.org/10.1145/3514094.3534134

Published: 27 July 2022 Publication History

Abstract

The proliferation of social media set the foundation for the culture of over-disclosure where many people document every single event, incident, trip, etc. for everyone to see. Raising the individual's awareness of the privacy issues that they are subjecting themselves to can be challenging. This becomes more complex when the post being shared includes data "owned" by others. The existing approaches aiming to assist users in multi-party disclosure situations need to be revised to go beyond preferences to the "good" of the collective.

This paper proposes an agent called Aegis to calculate the potential risk incurred by multi-party members in order to push privacy-preserving nudges to the sharer. Aegis is inspired by the consequentialist approach in normative ethical problem-solving techniques. The main contribution is the introduction of a social media-specific risk equation based on data valuation and the propagation of the post from intended to unintended audience. The proof-of-concept reports on how Aegis performs based on real-world data from the SNAP dataset and synthetically generated networks.

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Cited By

Salehzadeh Niksirat KKorka DHarkous HHuguenin KCherubini M(2023)On the Potential of Mediation Chatbots for Mitigating Multiparty Privacy Conflicts - A Wizard-of-Oz StudyProceedings of the ACM on Human-Computer Interaction10.1145/35796187:CSCW1(1-33)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579618
Ben Salem RAïmeur EHage H(2023)User modelling for privacy-aware self-disclosure2023 20th Annual International Conference on Privacy, Security and Trust (PST)10.1109/PST58708.2023.10320200(1-8)Online publication date: 21-Aug-2023
https://doi.org/10.1109/PST58708.2023.10320200

Index Terms

Aegis: An Agent for Multi-party Privacy Preservation
1. Security and privacy
  1. Human and societal aspects of security and privacy
    1. Privacy protections

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cover image ACM Conferences

AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

July 2022

939 pages

ISBN:9781450392471

DOI:10.1145/3514094

General Chairs:
Vincent Conitzer
Duke University & University of Oxford
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John Tasioulas
University of Oxford
,
Program Chairs:
Matthias Scheutz
Tufts University
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Ryan Calo
University of Washington
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Martina Mara
Johannes Kepler University Linz
,
Annette Zimmermann
University of York

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Published: 27 July 2022

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Canada?s Natural Sciences and Engineering Research Council (NSERC)

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AIES '22: AAAI/ACM Conference on AI, Ethics, and Society

May 19 - 21, 2021

Oxford, United Kingdom

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Overall Acceptance Rate 61 of 162 submissions, 38%

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Cited By

Salehzadeh Niksirat KKorka DHarkous HHuguenin KCherubini M(2023)On the Potential of Mediation Chatbots for Mitigating Multiparty Privacy Conflicts - A Wizard-of-Oz StudyProceedings of the ACM on Human-Computer Interaction10.1145/35796187:CSCW1(1-33)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579618
Ben Salem RAïmeur EHage H(2023)User modelling for privacy-aware self-disclosure2023 20th Annual International Conference on Privacy, Security and Trust (PST)10.1109/PST58708.2023.10320200(1-8)Online publication date: 21-Aug-2023
https://doi.org/10.1109/PST58708.2023.10320200

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