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JFlow: practical mostly-static information flow control

Open access
Myers, Andrew C.·1999·Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages

Abstract

A promising technique for protecting privacy and integrity of sensitive data is to statically check information flow within programs that manipulate the data. While previous work has proposed programming language extensions to allow this static checking, the resulting languages are too restrictive for practical use and have not been implemented. In this paper, we describe the new language JFlow, an extension to the Java language that adds statically-checked information flow annotations. JFlow provides several new features that make information flow checking more flexible and convenient than in previous models: a decentralized label model, label polymorphism, run-time label checking, and automatic label inference. JFlow also supports many language features that have never been integrated successfully with static information flow control, including objects, subclassing, dynamic type tests, access control, and exceptions. This paper defines the JFlow language and presents formal rules that are used to check JFlow programs for correctness. Because most checking is static, there is little code space, data space, or run-time overhead in the JFlow implementation.

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Metadata

Authors
Myers, A. C.
Venue
Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Publisher
ACM
Published
1999-01
Pages
228-241
OpenAlex
W2158126684
Cited by
1,034
References
21
FWCI
19.81
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: JFlow: practical mostly-static information flow control. https://app.cochat.ai/papers/10.1145/292540.292561
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Myers, A. C. (1999). JFlow: practical mostly-static information flow control. Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages. https://doi.org/10.1145/292540.292561

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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