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Privacy of Hidden Profiles: Utility-Preserving Profile Removal in Online Forums

Published: 06 November 2017 Publication History

Abstract

Users who wish to leave an online forum often do not have the freedom to erase their data completely from the service providers' (SP) system. The primary reason behind this is that analytics on such user data form a core component of many online providers' business models. On the other hand, if the profiles reside in the SP's system in an unchanged form, major privacy violations may occur if the infrastructure is compromised, or the SP is acquired by another organization. In this work, we investigate an alternative solution to standard profile removal, where posts of different users are split and merged into synthetic mediator profiles. The goal of our framework is to preserve the SP's data mining utility as far as possible, while minimizing users' privacy risks. We present several mechanisms of assigning user posts to such mediator accounts and show the effectiveness of our framework using data from StackExchange and various health forums.

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Cited By

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  • (2024)When graph convolution meets double attention: online privacy disclosure detection with multi-label text classificationData Mining and Knowledge Discovery10.1007/s10618-023-00992-y38:3(1171-1192)Online publication date: 1-May-2024
  • (2020)Fine-Grained Privacy Detection with Graph-Regularized Hierarchical Attentive Representation LearningACM Transactions on Information Systems10.1145/340610938:4(1-26)Online publication date: 16-Sep-2020
  • (2020)Operationalizing the Legal Principle of Data Minimization for PersonalizationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401034(399-408)Online publication date: 25-Jul-2020
  • Show More Cited By

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cover image ACM Conferences
CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
November 2017
2604 pages
ISBN:9781450349185
DOI:10.1145/3132847
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: 06 November 2017

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Author Tags

  1. mediator accounts
  2. privacy-utility tradeoff
  3. profile removal
  4. provider utility
  5. split and merge
  6. user privacy

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CIKM '17
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CIKM '17 Paper Acceptance Rate 171 of 855 submissions, 20%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all
  • (2024)When graph convolution meets double attention: online privacy disclosure detection with multi-label text classificationData Mining and Knowledge Discovery10.1007/s10618-023-00992-y38:3(1171-1192)Online publication date: 1-May-2024
  • (2020)Fine-Grained Privacy Detection with Graph-Regularized Hierarchical Attentive Representation LearningACM Transactions on Information Systems10.1145/340610938:4(1-26)Online publication date: 16-Sep-2020
  • (2020)Operationalizing the Legal Principle of Data Minimization for PersonalizationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401034(399-408)Online publication date: 25-Jul-2020
  • (2019)On Anonymous CommentingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331364(1225-1228)Online publication date: 18-Jul-2019
  • (2018) P 2 AM: An Anti-Profiling Framework for Online Healthcare Applications 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS)10.1109/ICSESS.2018.8663804(351-356)Online publication date: Nov-2018

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