A Privacy Guard Service

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dc.contributor.author Ye, Xin en
dc.contributor.author Wang, F en
dc.coverage.spatial Honolulu, HI, USA en
dc.date.accessioned 2018-10-08T00:33:37Z en
dc.date.issued 2017 en
dc.identifier.citation 2017 IEEE International Conference on Cognitive Computing, Honolulu, HI, USA, 26 Jun 2017 - 30 Jun 2017. 2017 IEEE International Conference on Cognitive Computing. IEEE. 48-55. 2017 en
dc.identifier.isbn 978-1-5386-2008-3 en
dc.identifier.uri http://hdl.handle.net/2292/39287 en
dc.description.abstract Mobile devices are changing the way that people conduct their daily businesses and carry out their works. More and more people are using mobile devices to view personal or work-related information in public places, e.g. café, train, etc. This type of information might contain sensitive data, e.g. personal information, trade secrets, etc. As high-resolution cameras are widely used and public places are always crowded, viewing information in public carries the risk of having the screen filmed by cameras or being peeked by the near-by people. This paper proposes a privacy guard service to help people to safe-guard their sensitive data while viewing information in public. The service uses machine learning and natural language processing techniques to identify sensitive information in documents. The service automatically converts the sensitive information to meaningless strings. Text-to-speech code is embedded behind the symbols. The code enable the users to listen to the content of the original sensitive information by using an earphone when the users tap on the symbols. As a result, users are able to view their sensitive data in public without worrying about privacy leaks due to visual observation attacks. en
dc.publisher IEEE en
dc.relation.ispartof 2017 IEEE International Conference on Cognitive Computing en
dc.relation.ispartofseries Proceedings 2017 IEEE International Conference on Cognitive Computing en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://www.ieee.org/publications/rights/author-posting-policy.html en
dc.title A Privacy Guard Service en
dc.type Conference Item en
dc.identifier.doi 10.1109/IEEE.ICCC.2017.14 en
pubs.begin-page 48 en
dc.rights.holder Copyright: IEEE en
pubs.end-page 55 en
pubs.finish-date 2017-06-30 en
pubs.start-date 2017-06-26 en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Proceedings en
pubs.elements-id 687049 en
pubs.org-id Science en
pubs.org-id School of Computer Science en
pubs.record-created-at-source-date 2017-10-09 en


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