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Precise, dynamic information flow for database-backed applications
ACM SIGPLAN Notices (2016)
  • Jean Yang, Massachusetts Institute of Technology
  • Travis Hance, Dropbox
  • Thomas H. Austin, San Jose State University
  • Armando Solar-Lezama, Massachusetts Institute of Technology
  • Cormac Flanagan, University of California, Santa Cruz
  • Stephen Chong, Harvard University
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.
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Citation Information
Jean Yang, Travis Hance, Thomas H. Austin, Armando Solar-Lezama, et al.. "Precise, dynamic information flow for database-backed applications" ACM SIGPLAN Notices (2016) p. 631 - 647
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