Privacy Monitoring Service for Conversations

Qiongkai Xu, Chenchen Xu, Lizhen Qu

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Citations (Scopus)

    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. A video record of our system demonstration is included in supplementary material and is also available at Google Drive.

    Original languageEnglish
    Title of host publicationWSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining
    PublisherAssociation for Computing Machinery, Inc
    Pages1093-1096
    Number of pages4
    ISBN (Electronic)9781450382977
    DOIs
    Publication statusPublished - 3 Aug 2021
    Event14th ACM International Conference on Web Search and Data Mining, WSDM 2021 - Virtual, Online, Israel
    Duration: 8 Mar 202112 Mar 2021

    Publication series

    NameWSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining

    Conference

    Conference14th ACM International Conference on Web Search and Data Mining, WSDM 2021
    Country/TerritoryIsrael
    CityVirtual, Online
    Period8/03/2112/03/21

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