Privacy monitoring service for conversations

Qiongkai Xu, Chenchen Xu, Lizhen Qu

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

2 Citations (Scopus)


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 '21
Subtitle of host publicationproceedings of the 14th ACM International Conference on Web Search and Data Mining
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450382977
Publication statusPublished - 2021
Externally publishedYes
Event14th ACM International Conference on Web Search and Data Mining, WSDM 2021 - Virtual, Online, Israel
Duration: 8 Mar 202112 Mar 2021


Conference14th ACM International Conference on Web Search and Data Mining, WSDM 2021
CityVirtual, Online


  • Privacy Preservation
  • Conversation
  • Information Retrieval


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