short-paper

Faking contextual data for fun, profit, and privacy

Authors:

Philippe GolleAuthors Info & Claims

WPES '09: Proceedings of the 8th ACM workshop on Privacy in the electronic society

Pages 105 - 108

https://doi.org/10.1145/1655188.1655204

Published: 09 November 2009 Publication History

Abstract

The amount of contextual data collected, stored, mined, and shared is increasing exponentially. Street cameras, credit card transactions, chat and Twitter logs, e-mail, web site visits, phone logs and recordings, social networking sites, all are examples of data that persists in a manner not under individual control, leading some to declare the death of privacy. We argue here that the ability to generate convincing fake contextual data can be a basic tool in the fight to preserve privacy. One use for the technology is for an individual to make his actual data indistinguishable amongst a pile of false data.

In this paper we consider two examples of contextual data, search engine query data and location data. We describe the current state of faking these types of data and our own efforts in this direction.

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Cited By

Nagarajan SDevarajan GMohammed ARamana TGhosh U(2023)Intelligent Task Scheduling Approach for IoT Integrated Healthcare Cyber Physical SystemsIEEE Transactions on Network Science and Engineering10.1109/TNSE.2022.322384410:5(2429-2438)Online publication date: 1-Sep-2023
https://doi.org/10.1109/TNSE.2022.3223844
Houssiau FLiénart THendrickx Jde Montjoye Y(2023)Web Privacy: A Formal Adversarial Model for Query ObfuscationIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326212318(2132-2143)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3262123
Pàmies-Estrems DGarcia-Alfaro J(2023)On the self-adjustment of privacy safeguards for query log streamsComputers & Security10.1016/j.cose.2023.103450134(103450)Online publication date: Nov-2023
https://doi.org/10.1016/j.cose.2023.103450
Show More Cited By

Index Terms

Faking contextual data for fun, profit, and privacy
1. Security and privacy
  1. Human and societal aspects of security and privacy
2. Social and professional topics
  1. Computing / technology policy
    1. Privacy policies

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Published In

cover image ACM Conferences

WPES '09: Proceedings of the 8th ACM workshop on Privacy in the electronic society

November 2009

130 pages

ISBN:9781605587837

DOI:10.1145/1655188

General Chair:
Ehab Al-Shaer
De Paul University, USA
,
Program Chair:
Stefano Paraboschi
Università di Bergamo, Italy

Copyright © 2009 ACM.

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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SIGSAC: ACM Special Interest Group on Security, Audit, and Control

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 November 2009

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CCS '09

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CCS '09: 16th ACM Conference on Computer and Communications Security 2009

November 9, 2009

Illinois, Chicago, USA

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Overall Acceptance Rate 106 of 355 submissions, 30%

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CCS '24

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October 14 - 18, 2024

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Cited By

Nagarajan SDevarajan GMohammed ARamana TGhosh U(2023)Intelligent Task Scheduling Approach for IoT Integrated Healthcare Cyber Physical SystemsIEEE Transactions on Network Science and Engineering10.1109/TNSE.2022.322384410:5(2429-2438)Online publication date: 1-Sep-2023
https://doi.org/10.1109/TNSE.2022.3223844
Houssiau FLiénart THendrickx Jde Montjoye Y(2023)Web Privacy: A Formal Adversarial Model for Query ObfuscationIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326212318(2132-2143)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3262123
Pàmies-Estrems DGarcia-Alfaro J(2023)On the self-adjustment of privacy safeguards for query log streamsComputers & Security10.1016/j.cose.2023.103450134(103450)Online publication date: Nov-2023
https://doi.org/10.1016/j.cose.2023.103450
Li STian HShen HSang Y(2023)Differential-Privacy Preserving Trajectory Data Publishing for Road NetworksRecent Challenges in Intelligent Information and Database Systems10.1007/978-3-031-42430-4_46(558-571)Online publication date: 29-Sep-2023
https://doi.org/10.1007/978-3-031-42430-4_46
Stach CGritti CBräcker JBehringer MMitschang B(2022)Protecting Sensitive Data in the Information Age: State of the Art and Future ProspectsFuture Internet10.3390/fi1411030214:11(302)Online publication date: 22-Oct-2022
https://doi.org/10.3390/fi14110302
Shenoy JLiu ZTao BKabelac ZVasisht DKuipers FOrda A(2022)RF-protectProceedings of the ACM SIGCOMM 2022 Conference10.1145/3544216.3544256(588-600)Online publication date: 22-Aug-2022
https://dl.acm.org/doi/10.1145/3544216.3544256
Jasim MShakhatreh HSiasi NSawalmeh AAldalbahi AAl-Fuqaha A(2022)A Survey on Spectrum Management for Unmanned Aerial Vehicles (UAVs)IEEE Access10.1109/ACCESS.2021.313804810(11443-11499)Online publication date: 2022
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Waniek MMagdy WRahwan T(2022)Hiding opinions from machine learningPNAS Nexus10.1093/pnasnexus/pgac2561:5Online publication date: 16-Nov-2022
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Li STian HShen HSang Y(2021)Privacy-Preserving Trajectory Data Publishing by Dynamic Anonymization with Bounded DistortionISPRS International Journal of Geo-Information10.3390/ijgi1002007810:2(78)Online publication date: 16-Feb-2021
https://doi.org/10.3390/ijgi10020078
Murakami THamada KKawamoto YHatano T(2021)Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific FeaturesProceedings on Privacy Enhancing Technologies10.2478/popets-2021-00152021:2(5-26)Online publication date: 29-Jan-2021
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