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Tagvisor: A Privacy Advisor for Sharing Hashtags

Authors:

Mathias Humbert,

Tahleen Rahman,

Michael BackesAuthors Info & Claims

WWW '18: Proceedings of the 2018 World Wide Web Conference

Pages 287 - 296

https://doi.org/10.1145/3178876.3186095

Published: 23 April 2018 Publication History

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Abstract

Hashtag has emerged as a widely used concept of popular culture and campaigns, but its implications on people»s privacy have not been investigated so far. In this paper, we present the first systematic analysis of privacy issues induced by hashtags. We concentrate in particular on location, which is recognized as one of the key privacy concerns in the Internet era. By relying on a random forest model, we show that we can infer a user»s precise location from hashtags with accuracy of 70% to 76%, depending on the city. To remedy this situation, we introduce a system called Tagvisor that systematically suggests alternative hashtags if the user-selected ones constitute a threat to location privacy. Tagvisor realizes this by means of three conceptually different obfuscation techniques and a semantics-based metric for measuring the consequent utility loss. Our findings show that obfuscating as little as two hashtags already provides a near-optimal trade-off between privacy and utility in our dataset. This in particular renders Tagvisor highly time-efficient, and thus, practical in real-world settings.

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Cited By

Vassøy BLangseth H(2024)Consumer-side fairness in recommender systems: a systematic survey of methods and evaluationArtificial Intelligence Review10.1007/s10462-023-10663-557:4Online publication date: 29-Mar-2024
https://doi.org/10.1007/s10462-023-10663-5
Li CLi CLin S(2023)Learning Privacy-Preserving Embeddings for Image Data to Be PublishedACM Transactions on Intelligent Systems and Technology10.1145/362340414:6(1-26)Online publication date: 14-Nov-2023
https://dl.acm.org/doi/10.1145/3623404
Dai RLuo JLuo XMo LMa WZhou F(2023)Multi-modal Representation Learning for Social Post Location InferenceICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10279649(6331-6336)Online publication date: 28-May-2023
https://doi.org/10.1109/ICC45041.2023.10279649
Show More Cited By

Index Terms

Tagvisor: A Privacy Advisor for Sharing Hashtags
1. Security and privacy
  1. Human and societal aspects of security and privacy
    1. Privacy protections
  2. Software and application security
    1. Social network security and privacy

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cover image ACM Other conferences

WWW '18: Proceedings of the 2018 World Wide Web Conference

April 2018

2000 pages

ISBN:9781450356398

General Chairs:
Pierre-Antoine Champin
Universitè Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

Copyright © 2018 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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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

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Published: 23 April 2018

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German Federal Ministry of Education and Research (BMBF)

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WWW '18

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IW3C2

WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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WWW '18 Paper Acceptance Rate 170 of 1,155 submissions, 15%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Vassøy BLangseth H(2024)Consumer-side fairness in recommender systems: a systematic survey of methods and evaluationArtificial Intelligence Review10.1007/s10462-023-10663-557:4Online publication date: 29-Mar-2024
https://doi.org/10.1007/s10462-023-10663-5
Li CLi CLin S(2023)Learning Privacy-Preserving Embeddings for Image Data to Be PublishedACM Transactions on Intelligent Systems and Technology10.1145/362340414:6(1-26)Online publication date: 14-Nov-2023
https://dl.acm.org/doi/10.1145/3623404
Dai RLuo JLuo XMo LMa WZhou F(2023)Multi-modal Representation Learning for Social Post Location InferenceICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10279649(6331-6336)Online publication date: 28-May-2023
https://doi.org/10.1109/ICC45041.2023.10279649
Li XChen LWu D(2023)Adversary for Social Good: Leveraging Attribute-Obfuscating Attack to Protect User Privacy on Social NetworksSecurity and Privacy in Communication Networks10.1007/978-3-031-25538-0_37(710-728)Online publication date: 4-Feb-2023
https://doi.org/10.1007/978-3-031-25538-0_37
Villarán CBeltrán M(2022)User-Centric Privacy for Identity Federations Based on a Recommendation SystemElectronics10.3390/electronics1108123811:8(1238)Online publication date: 14-Apr-2022
https://doi.org/10.3390/electronics11081238
Sumner BDorai GHeslen J(2022)Preliminary Analysis of Privacy Implications Observed in Social-Media Posts Across Shopping PlatformsProceedings of the 17th International Conference on Availability, Reliability and Security10.1145/3538969.3544457(1-10)Online publication date: 23-Aug-2022
https://dl.acm.org/doi/10.1145/3538969.3544457
Salem AWen RBackes MMa SZhang Y(2022)Dynamic Backdoor Attacks Against Machine Learning Models2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP53844.2022.00049(703-718)Online publication date: Jun-2022
https://doi.org/10.1109/EuroSP53844.2022.00049
Chen HLi C(2022)Predicting and Analyzing Privacy Settings and Categories for Posts on Social Media2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020677(5692-5697)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020677
Hsu CLi C(2021)RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential RecommendationProceedings of the Web Conference 202110.1145/3442381.3449957(2968-2979)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3442381.3449957
Hanzlik LZhang YGrosse KSalem AAugustin MBackes MFritz M(2021)MLCapsule: Guarded Offline Deployment of Machine Learning as a Service2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW53098.2021.00368(3295-3304)Online publication date: Jun-2021
https://doi.org/10.1109/CVPRW53098.2021.00368
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