Formal Modelling and Automated Trade-off Analysis of Enforcement Architectures for Cryptographic Access Control in the Cloud

Stefano Berlato, R. Carbone, Adam J. Lee, Silvio Ranise
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引用次数: 1

Abstract

To facilitate the adoption of cloud by organizations, Cryptographic Access Control (CAC) is the obvious solution to control data sharing among users while preventing partially trusted Cloud Service Providers (CSP) from accessing sensitive data. Indeed, several CAC schemes have been proposed in the literature. Despite their differences, available solutions are based on a common set of entities—e.g., a data storage service or a proxy mediating the access of users to encrypted data—that operate in different (security) domains—e.g., on-premise or the CSP. However, the majority of these CAC schemes assumes a fixed assignment of entities to domains; this has security and usability implications that are not made explicit and can make inappropriate the use of a CAC scheme in certain scenarios with specific trust assumptions and requirements. For instance, assuming that the proxy runs at the premises of the organization avoids the vendor lock-in effect but may give rise to other security concerns (e.g., malicious insiders attackers). To the best of our knowledge, no previous work considers how to select the best possible architecture (i.e., the assignment of entities to domains) to deploy a CAC scheme for the trust assumptions and requirements of a given scenario. In this article, we propose a methodology to assist administrators in exploring different architectures for the enforcement of CAC schemes in a given scenario. We do this by identifying the possible architectures underlying the CAC schemes available in the literature and formalizing them in simple set theory. This allows us to reduce the problem of selecting the most suitable architectures satisfying a heterogeneous set of trust assumptions and requirements arising from the considered scenario to a decidable Multi-objective Combinatorial Optimization Problem (MOCOP) for which state-of-the-art solvers can be invoked. Finally, we show how we use the capability of solving the MOCOP to build a prototype tool assisting administrators to preliminarily perform a “What-if” analysis to explore the trade-offs among the various architectures and then use available standards and tools (such as TOSCA and Cloudify) for automated deployment in multiple CSPs.
云中密码访问控制实施体系结构的形式化建模和自动权衡分析
为了促进组织采用云,加密访问控制(CAC)是控制用户之间数据共享的明显解决方案,同时防止部分受信任的云服务提供商(CSP)访问敏感数据。事实上,文献中已经提出了几种CAC方案。尽管存在差异,但可用的解决方案都基于一组共同的实体——例如。数据存储服务或代理,调解用户对加密数据的访问,这些数据在不同的(安全)域中操作。,内部部署或CSP。然而,这些CAC方案中的大多数都假定实体对域的固定分配;这对安全性和可用性的影响并不明确,并且在具有特定信任假设和需求的某些场景中可能会不适当地使用CAC方案。例如,假设代理在组织内部运行,可以避免供应商锁定效应,但可能会引起其他安全问题(例如,恶意的内部攻击者)。据我们所知,以前的工作没有考虑如何选择最好的架构(即,将实体分配到域)来部署CAC方案,以满足给定场景的信任假设和需求。在本文中,我们提出了一种方法来帮助管理员探索在给定场景中实施CAC方案的不同体系结构。我们通过识别文献中可用的CAC方案的可能架构并在简单集合理论中形式化它们来做到这一点。这使我们能够减少选择最合适的架构的问题,以满足从所考虑的场景中产生的异质信任假设和需求集,以确定多目标组合优化问题(MOCOP),其中可以调用最先进的求解器。最后,我们展示了如何使用解决MOCOP的能力来构建一个原型工具,帮助管理员初步执行“假设”分析,以探索各种体系结构之间的权衡,然后使用可用的标准和工具(如TOSCA和Cloudify)在多个csp中进行自动部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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