Security is increasingly critical in data communication of distributed environments. DDS is a middleware standard for data-centric publish/subscribe communication in a large scale real-time environment. DDS provides a security model for secure data communication. A major service of the security model is authorization. The authorization is based on the contents of messages rather than the information about the participant which should be the subject for access control. In this article, we present a novel approach for improved authorization of the DDS security model using ABAC. We first analyze the DDS security model and identify integration points for ABAC. Based on the analysis, we incorporate ABAC entities into the security model with ABAC behaviors defined across RTPS and DCPS. We implemented the model in XACML and evaluated by applying it to a patient monitoring system in the healthcare domain for its effectiveness, scalability, and efficiency in a controlled environment. The evaluation on effectiveness demonstrates that the model successfully enforces access control during the discovery process in a dynamic changing setting. The evaluation on scalability and efficiency demonstrates that the model is capable of handling 1,050 access requests simultaneously under the average of 40.60 milliseconds which satisfies the TT3 requirements in IEC 61850-5 with the average ABAC overheads of 10.62 milliseconds accounting for 26.67 percent of the communication time.

Class cohesion is a design quality that has a great impact on posterior development and maintenance of object-oriented systems. There have been much works on measuring class cohesion based on internal class relationships such as method-attribute referencing and internal method invocations. However, object-oriented systems involve many external class relationships carrying a functional context which should be also taken into account in measuring class cohesion. However, the existing works using internal relationships cannot measure cohesion of classes involving many external relationships. In this paper, we present a novel metric for measuring class cohesion based on both internal and external class relationships through an iterative process. We evaluate the metric by applying it to five applications — ArgoUML, jEdit, JHotDraw, JMeter, and Refactor, and validate the metric theoretically and statistically. The theoretical validation shows that the metric exhibits the required properties for cohesion metrics and the statistical validation shows that the metric captures a new aspect of class cohesion that has not been addressed by the existing works.