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Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics

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개인저자Benthall, Sebastian P.
단체저자명University of California, Berkeley. Information Management & Systems.
서명/저자사항Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics.
발행사항[S.l.] : University of California, Berkeley., 2018
발행사항Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항154 p.
소장본 주기School code: 0028.
ISBN9780438324374
일반주기 Source: Dissertation Abstracts International, Volume: 80-01(E), Section: A.
Advisers: John Chuang
요약The creators of technical infrastructure are under social and legal pressure to comply with expectations that can be difficult to translate into computational and business logics. This dissertation bridges this gap through three projects that fo
요약The first project studies privacy engineering's use of Contextual Integrity theory (CI), which defines privacy as appropriate information flow according to norms specific to social contexts or spheres. Computer scientists using CI have innovated
요약This concern inspires the second project, which addresses the problem of building computational systems that comply with data flow and security restrictions such as those required by law. Many privacy and data protection policies stipulate restr
요약The third project uses the causal modeling of information flow to address gaps in current theory of data economics. Like CI, privacy economics has focused on individual economic contexts and so has been unable to comprehend an information econom
일반주제명Information science.
Computer science.
Economics.
언어영어
기본자료 저록Dissertation Abstracts International80-01A(E).
Dissertation Abstract International
대출바로가기http://www.riss.kr/pdu/ddodLink.do?id=T14998092

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