Privacy monitoring service for conversations

Qiongkai Xu, Chenchen Xu, Lizhen Qu

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-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 publicationProceedings of the 14th ACM International Conference on Web Search and Data Mining
EditorsEugene Agichtein, Evgeniy Gabrilovich
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages1093-1096
Number of pages4
ISBN (Electronic)9781450382977
DOIs
Publication statusPublished - 2021
EventACM International Conference on Web Search and Data Mining 2021 - Online, Israel
Duration: 8 Mar 202112 Mar 2021
Conference number: 14th
https://dl.acm.org/doi/proceedings/10.1145/3437963 (Proceedings)
https://www.wsdm-conference.org/2021/ (Website)

Conference

ConferenceACM International Conference on Web Search and Data Mining 2021
Abbreviated titleWSDM 2021
Country/TerritoryIsrael
Period8/03/2112/03/21
Internet address

Keywords

  • conversation
  • information retrieval
  • privacy preservation

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