Language-based information-flow security
Abstract
Current standard security practices do not provide substantial assurance that the end-to-end behavior of a computing system satisfies important security policies such as confidentiality. An end-to-end confidentiality policy might assert that secret input data cannot be inferred by an attacker through the attacker's observations of system output; this policy regulates information flow. Conventional security mechanisms such as access control and encryption do not directly address the enforcement of information-flow policies. Previously, a promising new approach has been developed: the use of programming-language techniques for specifying and enforcing information-flow policies. In this paper, we survey the past three decades of research on information-flow security, particularly focusing on work that uses static program analysis to enforce information-flow policies. We give a structured view of work in the area and identify some important open challenges.
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As tasks are decomposed across agents, intermediate outputs may implicitly encode or propagate sensitive information beyond intended scopes, creating implicit information flows that bypass explicit access controls.
“As tasks are decomposed across agents, intermediate outputs (e.g., summaries, plans, or tool calls) may implicitly encode or propagate sensitive information beyond intended scopes, creating implicit information flows that bypass explicit access controls (Denning, 1976;Sabelfeld & Myers, 2003).”
From Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents (2025) · cites this paper as Sabelfeld & Myers, 2003
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Noninterference through Secure Multi-execution
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Self-citationDynamic Taint Propagation for Java
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Secure information flow by self-composition
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Automatic Discovery and Quantification of Information Leaks
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seL4: From General Purpose to a Proof of Information Flow Enforcement
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A Model for Delimited Information Release
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Self-citationEfficient purely-dynamic information flow analysis
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Dynamic vs. Static Flow-Sensitive Security Analysis
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Self-citationSecure information flow by self-composition
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AppContext: Differentiating Malicious and Benign Mobile App Behaviors Using Context
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Cloud Data Protection for the Masses
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Self-citationIronclad apps: end-to-end security via automated full-system verification
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Consistency Analysis in Bloom: a CALM and Collected Approach
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Self-citationFlexible dynamic information flow control in Haskell
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Self-citationThe taser intrusion recovery system
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Stack-based access control and secure information flow
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Quantitative Information Flow, Relations and Polymorphic Types
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Tight Enforcement of Information-Release Policies for Dynamic Languages
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Andromeda: Accurate and Scalable Security Analysis of Web Applications
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Efficient and extensible security enforcement using dynamic data flow analysis
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Permissive dynamic information flow analysis
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Separating agreement from execution for byzantine fault tolerant services
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A logic for information flow in object-oriented programs
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Language-based control and mitigation of timing channels
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Self-citationSome Recipes Can Do More Than Spoil Your Appetite
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Assessing and Improving Malware Detection Sustainability through App Evolution Studies
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Automata-Based Confidentiality Monitoring
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Speculative Taint Tracking (STT)
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A Formal Foundation for Secure Remote Execution of Enclaves
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Cartesian hoare logic for verifying k-safety properties
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Digital twins, big data governance, and sustainable tourism
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The taser intrusion recovery system
Goel, A., Po, K., Farhadi, K., Li, Z., & de Lara, E. (2005) · ACM SIGOPS Symposium on Operating Systems Principles (SOSP) · doi:10.1145/1095810.1095826 · Cited by 116 · see citing works
From Dynamic to Static and Back: Riding the Roller Coaster of Information-Flow Control Research
Sabelfeld, A., & Russo, A. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-11486-1_30 · Cited by 115 · see citing works
Self-citationLiu, C., Harris, A., Maas, M., Hicks, M., Tiwari, M., & Shi, E. (2015) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/2694344.2694385 · Cited by 114 · see citing works
Clarkson, M. R., & Schneider, F. B. (2008) · IEEE Computer Security Foundations Workshop (CSFW) · doi:10.1109/csf.2008.7 · Cited by 114 · see citing works
Using replication and partitioning to build secure distributed systems
Zheng, L., Chong, S., Myers, A. C., & Zdancewic, S. (2004) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/secpri.2003.1199340 · Cited by 113 · see citing works
Self-citationFable: A Language for Enforcing User-defined Security Policies
Swamy, N., Corcoran, B. J., & Hicks, M. (2008) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp.2008.29 · Cited by 112 · see citing works
Tightlip: keeping applications from spilling the beans
Yumerefendi, A. R., Mickle, B., & Cox, L. P. (2007) · Cited by 110 · see citing works
CacheAudit: A Tool for the Static Analysis of Cache Side Channels.
Doychev, G., Feld, D., Köpf, B., Mauborgne, L., & Reineke, J. (2013) · Cited by 109 · see citing works
- Authors
- Sabelfeld, A., & Myers, A. C.
- Affiliations
- Cornell University (US)
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2003-01
- Volume
- 21
- Issue
- 1
- Pages
- 5-19
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W2122049982
- Cited by
- 1,907
- References
- 164
- Citations by year
- 2026: 29 · 2025: 38 · 2024: 45 · 2023: 43 · 2022: 50 · 2021: 65 · 2020: 56 · 2019: 87 · 2018: 67 · 2017: 83 · 2016: 77 · 2015: 101 · 2014: 135 · 2013: 105 · 2012: 122
- FWCI
- 97.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal on Selected Areas in Communications (publishedVersion)
- Funders
- Alfred P. Sloan Foundation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Security and Verification in Computing
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, programming, and type systems
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Keywords
- information flow security, confidentiality, static analysis, information flow policies, programming languages, policy enforcement, end-to-end security, open problems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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