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Privacy Monitoring Service for Conversations

Published: 08 March 2021 Publication History

Abstract

Leakage of personal information in conversations raises serious privacy concerns. Malicious people or bots could pry into sensitive personal information of vulnerable people, such as juveniles, through conversations with them or their digital personal assistants. To address the problem, we present a privacy-leakage warning system that monitors conversations in social media and intercepts the outgoing text messages from a user or a digital assistant, if they impose potential privacy leakage risks. Such messages are redirected to authorized users for approval, before they are sent out. We demonstrate how our system is deployed and used on a social media conversation platform, e.g., Facebook Messenger.

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Cited By

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  • (2022)Trust and digital privacy: willingness to disclose personal information to banking chatbot servicesJournal of Financial Services Marketing10.1057/s41264-022-00154-z28:2(337-357)Online publication date: 25-Apr-2022
  • (2022)Privacy Preservation Technique Based on Sensitivity Levels for Multiple Numerical Sensitive Overlapped AttributesHybrid Intelligent Systems10.1007/978-3-030-96305-7_5(38-55)Online publication date: 4-Mar-2022

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Published In

cover image ACM Conferences
WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining
March 2021
1192 pages
ISBN:9781450382977
DOI:10.1145/3437963
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 March 2021

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Author Tags

  1. conversation
  2. information retrieval
  3. privacy preservation

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WSDM '21

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Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

View all
  • (2022)Trust and digital privacy: willingness to disclose personal information to banking chatbot servicesJournal of Financial Services Marketing10.1057/s41264-022-00154-z28:2(337-357)Online publication date: 25-Apr-2022
  • (2022)Privacy Preservation Technique Based on Sensitivity Levels for Multiple Numerical Sensitive Overlapped AttributesHybrid Intelligent Systems10.1007/978-3-030-96305-7_5(38-55)Online publication date: 4-Mar-2022

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