NDLI: YouProve: authenticity and fidelity in mobile sensing

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YouProve: authenticity and fidelity in mobile sensing

Content Provider	ACM Digital Library
Author	Qin, Henry Gilbert, Peter Lee, Kyungmin Cox, Landon P. Sheth, Anmol Sharkey, Daniel Jung, Jaeyeon
Abstract	As more services have come to rely on sensor data such as audio and photos collected by mobile phone users, verifying the authenticity of this data has become critical for service correctness. At the same time, clients require the flexibility to tradeoff the fidelity of the data they contribute for resource efficiency or privacy. This paper describes YouProve, a partnership between a mobile device's trusted hardware and software that allows untrusted client applications to directly control the fidelity of data they upload and services to verify that the meaning of source data is preserved. The key to our approach is trusted analysis of derived data, which generates statements comparing the content of a derived data item to its source. Experiments with a prototype implementation for Android demonstrate that YouProve is feasible. Our photo analyzer is over 99% accurate at identifying regions changed only through meaning-preserving modifications such as cropping, compression, and scaling. Our audio analyzer is similarly accurate at detecting which sub-clips of a source audio clip are present in a derived version, even in the face of compression, normalization, splicing, and other modifications. Finally, performance and power costs are reasonable, with analyzers having little noticeable effect on interactive applications and CPU-intensive analysis completing asynchronously in under 70 seconds for 5-minute audio clips and under 30 seconds for 5-megapixel photos.
Starting Page	176
Ending Page	189
Page Count	14
File Format	PDF MP4
ISBN	9781450307185
DOI	10.1145/2070942.2070961
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Privacy Trusted computing Participatory sensing
Content Type	Audio Text
Resource Type	Article

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