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δ-Risk: Toward Context-aware Multi-objective Privacy Management in Connected Environments

Authors:

Karam Bou-Chaaya,

Richard Chbeir,

Mansour Naser Alraja,

Philippe Arnould,

Charith Perera,

Mahmoud Barhamgi,

Djamal BenslimaneAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 21, Issue 2

Article No.: 51, Pages 1 - 31

https://doi.org/10.1145/3418499

Published: 24 May 2021 Publication History

Abstract

In today’s highly connected cyber-physical environments, users are becoming more and more concerned about their privacy and ask for more involvement in the control of their data. However, achieving effective involvement of users requires improving their privacy decision-making. This can be achieved by: (i) raising their awareness regarding the direct and indirect privacy risks they accept to take when sharing data with consumers; (ii) helping them in optimizing their privacy protection decisions to meet their privacy requirements while maximizing data utility. In this article, we address the second goal by proposing a user-centric multi-objective approach for context-aware privacy management in connected environments, denoted δ-Risk. Our approach features a new privacy risk quantification model to dynamically calculate and select the best protection strategies for the user based on her preferences and contexts. Computed strategies are optimal in that they seek to closely satisfy user requirements and preferences while maximizing data utility and minimizing the cost of protection. We implemented our proposed approach and evaluated its performance and effectiveness in various scenarios. The results show that δ-Risk delivers scalability and low-complexity in time and space. Besides, it handles privacy reasoning in real-time, making it able to support the user in various contexts, including ephemeral ones. It also provides the user with at least one best strategy per context.

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Cited By

Yessoufou FChicha ESassi SChbeir RHounsou J(2023)CROWDPRED: Privacy-Preserving Approach for locations on Decentralized Crowdsourcing Application2023 International Conference on Innovations in Intelligent Systems and Applications (INISTA)10.1109/INISTA59065.2023.10310558(1-6)Online publication date: 20-Sep-2023
https://doi.org/10.1109/INISTA59065.2023.10310558
Long YLuo XZhu YLee KWang S(2023)Data Transparency Design in Internet of Things: A Systematic ReviewInternational Journal of Human–Computer Interaction10.1080/10447318.2023.222899740:18(5003-5025)Online publication date: 18-Jul-2023
https://doi.org/10.1080/10447318.2023.2228997

Index Terms

δ-Risk: Toward Context-aware Multi-objective Privacy Management in Connected Environments
1. Security and privacy
  1. Security services
    1. Privacy-preserving protocols
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Continuous optimization

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Information & Contributors

Information

Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 21, Issue 2

June 2021

599 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3453144

Editor:
Ling Liu
Georgia Institute of Technology, USA

Issue’s Table of Contents

Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 May 2021

Accepted: 01 August 2020

Revised: 01 August 2020

Received: 01 April 2020

Published in TOIT Volume 21, Issue 2

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Sultanate of Oman (Block Fund-Research Grant)

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Cited By

Yessoufou FChicha ESassi SChbeir RHounsou J(2023)CROWDPRED: Privacy-Preserving Approach for locations on Decentralized Crowdsourcing Application2023 International Conference on Innovations in Intelligent Systems and Applications (INISTA)10.1109/INISTA59065.2023.10310558(1-6)Online publication date: 20-Sep-2023
https://doi.org/10.1109/INISTA59065.2023.10310558
Long YLuo XZhu YLee KWang S(2023)Data Transparency Design in Internet of Things: A Systematic ReviewInternational Journal of Human–Computer Interaction10.1080/10447318.2023.222899740:18(5003-5025)Online publication date: 18-Jul-2023
https://doi.org/10.1080/10447318.2023.2228997

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