{"id":511778,"date":"2018-10-14T23:59:42","date_gmt":"2018-10-15T06:59:42","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=511778"},"modified":"2018-10-17T08:12:50","modified_gmt":"2018-10-17T15:12:50","slug":"privacyshield-a-mobile-system-for-supporting-subtle-just-in-time-privacy-provisioning-through-off-screen-based-touch-gestures","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/privacyshield-a-mobile-system-for-supporting-subtle-just-in-time-privacy-provisioning-through-off-screen-based-touch-gestures\/","title":{"rendered":"PrivacyShield: A Mobile System for Supporting Subtle Just-in-time Privacy Provisioning through Off-Screen-based Touch Gestures"},"content":{"rendered":"<p>Current in-situ privacy solution approaches are inadequate in protecting sensitive information. They either require extra<br \/>\nconfiguration effort or lack the ability to configure user desired privacy settings. Based on in-depth discussions during a design<br \/>\nworkshop, we propose PrivacyShield, a mobile system for providing subtle just-in-time privacy provisioning. PrivacyShield<br \/>\nleverages the screen I\/O device (screen digitizer) of smartphones to recognize gesture commands, even when the phone\u2019s screen<br \/>\nis turned off. Based on gesture command inputs, various privacy-protection policies can be configured on-the-fly. We develop<br \/>\na novel stroke-based approach to address the challenges in segmenting and recognizing gesture command inputs, which<br \/>\nhelps the system in achieving good usability and performance. PrivacyShield also provides developers with APIs to enable<br \/>\njust-in-time privacy provisioning in their applications. We have implemented an energy efficient PrivacyShield prototype on<br \/>\nthe Android platform, including smartphones with and without a low-power co-processor. Evaluation results show that our<br \/>\ngesture segmentation algorithm is fast enough for real-time performance (introducing less than 200ms processing latency)<br \/>\nand accurate (achieving an accuracy of 95% for single-character gestures and 89% for even three-character gestures). We also<br \/>\nbuild a non-touch-screen-based just-in-time privacy provisioning prototype called the wrist gesture method. We compare the<br \/>\nperformance of the two prototypes by doing a 6-week field study with 12 participants and show why a simplistic solution<br \/>\nfalls short in providing privacy configurations. We also report the participants\u2019 perceptions and reactions after the field study.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Current in-situ privacy solution approaches are inadequate in protecting sensitive information. They either require extra configuration effort or lack the ability to configure user desired privacy settings. Based on in-depth discussions during a design workshop, we propose PrivacyShield, a mobile system for providing subtle just-in-time privacy provisioning. PrivacyShield leverages the screen I\/O device (screen digitizer) [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"ACM \u2013 Association for Computing Machinery","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"UbiComp 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