Access control policies are usually specified by the XACML language. However, policy definition could be an error prone process, because of the many constraints and rules that have to be specified. In order to increase the confidence on defined XACML policies, an accurate testing activity could be a valid solution. The typical policy testing is performed by deriving specific test cases, i.e. XACML requests, that are executed by means of a PDP implementation, so to evidence possible security lacks or problems. Thus the fault detection effectiveness of derived test suite is a fundamental property. To evaluate the performance of the applied test strategy and consequently of the test suite, a commonly adopted methodology is using mutation testing. In this paper, we propose two different methodologies for deriving XACML requests, that are defined independently from the policy under test. The proposals exploit the values of the XACML policy for better customizing the generated requests and providing a more effective test suite. The proposed methodologies have been compared in terms of their fault detection effectiveness by the application of mutation testing on a set of real policies.

The trustworthiness of sensitive data needs to be guaranteed and testing is a common activity among privacy protection solutions, even if quite expensive. Accesses to data and resources are ruled by the policy decision point (PDP), which relies on the eXtensible Access Control Markup Language (XACML) standard language for specifying access rights. In this study, the authors propose a testing strategy for automatically deriving test requests from a XACML policy and describe their pilot experience in test automation using this strategy. Considering a real two‐level PDP implemented for health data security, the authors compare the effectiveness of the test plan automatically derived with the one derived by a standard manual testing process.

The growing availability of mobile devices has lead to an arising development of smart cities services that share a huge amount of (personal) information and data. Without accurate and verified management, they could become severe back-doors for security and privacy. In this paper, we propose a smart city infrastructure able to integrate a distributed privacy-preserving identity management solution based on attribute-based credentials (p-ABC), a user-centric Consent Manager, and a GDPR-based Access Control mechanism so as to guarantee the enforcement of the GDPR’s provisions. Thus, the infrastructure supports the definition of specific purpose, collection of data, regulation of access to personal data, and users’ consents, while ensuring selective and minimal disclosure of personal information as well as user’s unlinkability across service and identity providers. The proposal has been implemented, integrated, and evaluated in a fully-fledged environment consisting of MiMurcia, the Smart City project for the city of Murcia, CaPe, an industrial consent management system, and GENERAL_D, an academic GDPR-based access control system, showing the feasibility.

Testing of security policies is a critical activity and mutation analysis is an effective approach for measuring the adequacy of a test suite. In this paper, we propose a set of mutation operators addressing specific faults of the XACML 2.0 access control policy and a tool, called XACMUT (XACml MUTation) for creating mutants. The tool generates the set of mutants, provides facilities to run a given test suite on the mutants set and computes the test suite effectiveness in terms of mutation score. The tool includes and enhances the mutation operators of existing security policy mutation approaches.

Context: Access control is among the most important security mechanisms, and XACML is the de facto standard for specifying, storing and deploying access control policies. Since it is critical that enforced policies are correct, policy testing must be performed in an effective way to identify potential security flaws and bugs. In practice, exhaustive testing is impossible due to budget constraints. Therefore the tests need to be prioritized so that resources are focused on their most relevant subset. Objective: This paper tackles the issue of access control test prioritization. It proposes a new approach for access control test prioritization that relies on similarity. Method: The approach has been applied to several policies and the results have been compared to random prioritization (as a baseline). To assess the different prioritization criteria, we use mutation analysis and compute the mutation scores reached by each criterion. This helps assessing the rate of fault detection. Results: The empirical results indicate that our proposed approach is effective and its rate of fault detection is higher than that of random prioritization. Conclusion: We conclude that prioritization of access control test cases can be usefully based on similarity criteria