A Framework for the Cryptographic Enforcement of Information Flow Policies. / Alderman, James; Crampton, Jason; Farley, Naomi.

Proceedings of the 22nd ACM on Symposium on Access Control Models and Technologies. ACM, 2017. p. 143-154.

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Abstract

It is increasingly common to outsource data storage to untrusted, third party (e.g. cloud) servers. However, in such settings, low-level online reference monitors may not be appropriate for enforcing read access, and thus cryptographic enforcement schemes (CESs) may be required. Much of the research on cryptographic access control has focused on the use of specific primitives and, primarily, on how to generate appropriate keys and fails to model the access control system as a whole. Recent work in the context of role-based access control has shown a gap between theoretical policy specification and computationally secure implementations of access control policies, potentially leading to insecure implementations. Without a formal model, it is hard to (i) reason about the correctness and security of a CES, and (ii) show that the security properties of a particular cryptographic primitive are sufficient to guarantee security of the CES as a whole.

In this paper, we provide a rigorous definitional framework for a CES that enforces read-only information flow policies (which encompass many practical forms of access control, including role-based policies). This framework (i) provides a tool by which instantiations of CESs can be proven correct and secure, (ii) is independent of any particular cryptographic primitives used to instantiate a CES, and (iii) helps to identify the limitations of current primitives (e.g. key assignment schemes) as components of a CES.
Original languageEnglish
Title of host publicationProceedings of the 22nd ACM on Symposium on Access Control Models and Technologies
PublisherACM
Pages143-154
Number of pages12
ISBN (Print)978-1-4503-4702-0
DOIs
Publication statusPublished - 7 Jun 2017
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 28493809