Precise, dynamic information flow for database-backed applications

We present an approach for dynamic information flow control across the application and database. Our approach reduces the amount of policy code required, yields formal guarantees across the application and database, works with existing relational database implementations, and scales for realistic ap...

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Bibliographic Details
Main Authors: Yang, Jean (Author), Hance, Travis (Author), Austin, Thomas H. (Author), Flanagan, Cormac (Author), Chong, Stephen (Author), Solar Lezama, Armando (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery, 2017-12-29T19:45:12Z.
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Description
Summary:We present an approach for dynamic information flow control across the application and database. Our approach reduces the amount of policy code required, yields formal guarantees across the application and database, works with existing relational database implementations, and scales for realistic applications. In this paper, we present a programming model that factors out information flow policies from application code and database queries, a dynamic semantics for the underlying $^JDB$ core language, and proofs of termination-insensitive non-interference and policy compliance for the semantics. We implement these ideas in Jacqueline, a Python web framework, and demonstrate feasibility through three application case studies: a course manager, a health record system, and a conference management system used to run an academic workshop. We show that in comparison to traditional applications with hand-coded policy checks, Jacqueline applications have 1) a smaller trusted computing base, 2) fewer lines of policy code, and 2) reasonable, often negligible, additional overheads. Keywords: Web frameworks, information flow
Facebook (Fellowship)
Levine (Fellowship)
Qatar Computing Research Institute
National Science Foundation (U.S.) (Grant 1054172)
National Science Foundation (U.S.) (Grant CCF-1139056)
National Science Foundation (U.S.) (Grant CCF-1337278)
National Science Foundation (U.S.) (Grant CCF-1421016)