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Assuring Data Authenticity While Preserving User Choice in Mobile Sensing
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Assuring Data Authenticity While Preserving User Choice in Mobile Sensing. |
| 개인저자 | Gilbert, Peter. |
| 단체저자명 | Duke University. Computer Science. |
| 발행사항 | [S.l.]: Duke University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 106 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-09B(E). Dissertation Abstract International |
| ISBN | 9780355870145 |
| 학위논문주기 | Thesis (Ph.D.)--Duke University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Adviser: Landon P. Cox. |
| 이용제한사항 | This item is not available from ProQuest Dissertations & Theses. |
| 요약 | As more services have come to rely on sensor data such as photos and audio collected by mobile phone users, verifying the authenticity of this data has become critical for service correctness. At the same time, contributors require the flexibili |
| 요약 | To address certain cases where YouProve's approach is insufficient for evaluating modifications to photos, we introduce an alternative approach called pixel tracking. Pixel tracking uses dynamic taint analysis, or taint tracking, to monitor the |
| 요약 | Experiments with prototype implementations of YouProve and pixel tracking for Android demonstrate that the approaches are feasible. YouProve's photo analyzer is over 99% accurate at identifying regions changed only through meaning-preserving mod |
| 요약 | Our work on YouProve and pixel tracking demonstrates that it is possible to provide guarantees about data authenticity while preserving users' control over the data they contribute. |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
