Daoudagh S., Lonetti F., Marchetti E.
Access control Automated oracle derivation Testing Indexed keywords Risk Request generation Software Safety Reliability and Quality
In the context of access control systems, testing activity is among the most adopted means to assure that sensible information or resources are correctly accessed. In XACML-based access control systems, incoming access requests are transmitted to the policy decision point (PDP) that grants or denies the access based on the defined XACML policies. The criticality of a PDP component requires an intensive testing activity consisting in probing such a component with a set of requests and checking whether its responses grant or deny the requested access as specified in the policy. Existing approaches for improving manual derivation of test requests such as combinatorial ones do not consider policy function semantics and do not provide a verdict oracle. In this paper, we introduce XACMET, a novel approach for systematic generation of XACML requests as well as automated model-based oracle derivation. The main features of XACMET are as follows: (i) it defines a typed graph, called the XAC-Graph, that models the XACML policy evaluation; (ii) it derives a set of test requests via full-path coverage of this graph; (iii) it derives automatically the expected verdict of a specific request execution by executing the corresponding path in such graph; (iv) it allows us to measure coverage assessment of a given test suite. Our validation of the XACMET prototype implementation confirms the effectiveness of the proposed approach.
Source: Software quality journal 28 (2020): 249–282. doi:10.1007/s11219-019-09470-5
Publisher: Chapman & Hall,, London , Regno Unito
@article{oai:it.cnr:prodotti:424582, title = {XACMET: XACML Testing \& Modeling: An automated model-based testing solution for access control systems}, author = {Daoudagh S. and Lonetti F. and Marchetti E.}, publisher = {Chapman \& Hall,, London , Regno Unito}, doi = {10.1007/s11219-019-09470-5}, journal = {Software quality journal}, volume = {28}, pages = {249–282}, year = {2020} }