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FlyByNight: mitigating the privacy risks of social networking

Published: 27 October 2008 Publication History

Abstract

Social networking websites are enormously popular, but they present a number of privacy risks to their users, one of the foremost of which being that social network service providers are able to observe and accumulate the information that users transmit through the network. We aim to mitigate this risk by presenting a new architecture for protecting information published through the social networking website, Facebook, through encryption. Our architecture makes a trade-off between security and usability in the interests of minimally affecting users' workflow and maintaining universal accessibility. While active attacks by Facebook could compromise users' privacy, our architecture dramatically raises the cost of such potential compromises and, importantly, places them within a framework for legal privacy protection because they would violate a user's reasonable expectation of privacy. We have built a prototype Facebook application implementing our architecture, addressing some of the limitations of the Facebook platform through proxy cryptography.

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Blaze, M., G. Bleumer, and M. Strauss. Divertible Protocols and Atomic Proxy Cryptography. Lecture notes in computer science, pages 127--144.
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Cited By

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  • (2024)Use & Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy ExperimentationJournal of Cybersecurity and Privacy10.3390/jcp40300264:3(546-571)Online publication date: 11-Aug-2024
  • (2023)Enhancing privacy for automatically detected quasi identifier using data anonymizationWeb Intelligence10.3233/WEB-22182321:1(71-91)Online publication date: 22-Mar-2023
  • (2022)PosterProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3563541(3499-3501)Online publication date: 7-Nov-2022
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Published In

cover image ACM Conferences
WPES '08: Proceedings of the 7th ACM workshop on Privacy in the electronic society
October 2008
128 pages
ISBN:9781605582894
DOI:10.1145/1456403
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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Publication History

Published: 27 October 2008

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Author Tags

  1. privacy
  2. social networks

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Overall Acceptance Rate 106 of 355 submissions, 30%

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Cited By

View all
  • (2024)Use & Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy ExperimentationJournal of Cybersecurity and Privacy10.3390/jcp40300264:3(546-571)Online publication date: 11-Aug-2024
  • (2023)Enhancing privacy for automatically detected quasi identifier using data anonymizationWeb Intelligence10.3233/WEB-22182321:1(71-91)Online publication date: 22-Mar-2023
  • (2022)PosterProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3563541(3499-3501)Online publication date: 7-Nov-2022
  • (2022)Image DePO: Towards Gradual Decentralization of Online Social Networks using Decentralized Privacy OverlaysProceedings of the ACM on Human-Computer Interaction10.1145/35129076:CSCW1(1-28)Online publication date: 7-Apr-2022
  • (2022)Privacy protection scheme for mobile social networkJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2022.05.01134:7(4062-4074)Online publication date: Jul-2022
  • (2021)Privacy-Enhancing k-Nearest Neighbors Search over Mobile Social NetworksSensors10.3390/s2112399421:12(3994)Online publication date: 9-Jun-2021
  • (2021)A Survey : Data Mining and Machine Learning Methods for Cyber SecurityInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT217212(24-34)Online publication date: 1-Mar-2021
  • (2021)A novel blockchain-based privacy-preserving framework for online social networksConnection Science10.1080/09540091.2020.1854181(1-21)Online publication date: 7-Jan-2021
  • (2021)A Framework for Protecting Privacy on Mobile Social NetworksMobile Networks and Applications10.1007/s11036-021-01761-1Online publication date: 29-May-2021
  • (2021)Concealed Communication in Online Social NetworksApplied Cryptography in Computer and Communications10.1007/978-3-030-80851-8_9(117-137)Online publication date: 5-Jul-2021
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