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Cited by 556

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Protecting privacy using the decentralized label model

Open access
Myers, Andrew C., Liskov, Barbara·2000·ACM Transactions on Software Engineering and Methodology

Abstract

Stronger protection is needed for the confidentiality and integrity of data, because programs containing untrusted code are the rule rather than the exception. Information flow control allows the enforcement of end-to-end security policies, but has been difficult to put into practice. This article describes the decentralized label model, a new label model for control of information flow in systems with mutual distrust and decentralized authority. The model improves on existing multilevel security models by allowing users to declassify information in a decentralized way, and by improving support for fine-grained data sharing. It supports static program analysis of information flow, so that programs can be certified to permit only acceptable information flows, while largely avoiding the overhead of run-time checking. The article introduces the language Jif, an extension to Java that provides static checking of information flow using the decentralized label model.

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Metadata

Authors
Myers, A. C., & Liskov, B.
Venue
ACM Transactions on Software Engineering and Methodology
Published
2000-10
Volume
9
Issue
4
Pages
410-442
ISSN
  • 1049-331X (ISSN-L)
  • 1557-7392
OpenAlex
W2154564703
Cited by
556
References
1
FWCI
12.08
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Protecting privacy using the decentralized label model. https://app.cochat.ai/papers/10.1145/363516.363526
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Myers, A. C., & Liskov, B. (2000). Protecting privacy using the decentralized label model. ACM Transactions on Software Engineering and Methodology. https://doi.org/10.1145/363516.363526

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

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.