{"id":165191,"date":"2012-06-01T00:00:00","date_gmt":"2012-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/software-abstractions-for-trusted-sensors\/"},"modified":"2018-10-16T21:44:03","modified_gmt":"2018-10-17T04:44:03","slug":"software-abstractions-for-trusted-sensors","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/software-abstractions-for-trusted-sensors\/","title":{"rendered":"Software Abstractions for Trusted Sensors"},"content":{"rendered":"
\n

With the proliferation of e-commerce, e-wallet, and e-health smartphone applications, the need for trusted mobile applications is greater than ever. Unlike their desktop counterparts, many mobile applications rely heavily on sensor inputs. As a result, trust often requires authenticity and integrity of sensor readings. For example, applications may need trusted readings from sensors such as a GPS, camera, or microphone. Recent research has started to recognize the need for \u201ctrusted sensors\u201d, yet providing the right programming abstractions and system support for building mobile trusted applications is an open problem.<\/p>\n

This paper proposes two software abstractions for offering trusted sensors to mobile applications. We present the design and implementation of these abstractions on both x86 and ARM platforms. We implement a trusted GPS sensor on both platforms, and we provide a privacy control for trusted location using differential privacy. Our evaluation shows that implementing these abstractions comes with moderate overhead on both x86 and ARM platforms. We find these software abstractions to be versatile and practical \u2013 using them we implement one novel enterprise mobile application.<\/p>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

With the proliferation of e-commerce, e-wallet, and e-health smartphone applications, the need for trusted mobile applications is greater than ever. Unlike their desktop counterparts, many mobile applications rely heavily on sensor inputs. As a result, trust often requires authenticity and integrity of sensor readings. For example, applications may need trusted readings from sensors such as […]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-165191","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"ACM International Conference in Mobile Systems, Applications, and Services 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