## 9 Conclusions and Future Perspectives  
Although over the past decade security researchers have proposed a variety of policy models and metamodels to address real-world security problems, the limited ability of the existing AC methods to generically specify, upgrade, and enforce policy persists. With the IoT and industry 4.0, along with the digital transformation, where resources are widely distributed and must be accessed from anywhere, at any time, the need for secure information sharing has increased dramatically. Moreover, the evolution of pervasive ISs and intelligent manufacturing has had a significant impact on different directions, such as the industry's future. Smart industries combine various physical and cyber technologies to enhance productivity, performance, quality, and management. In this context, controlling access to protect resources from unauthorized use is a complicated and challenging task, especially with cybercriminals and cyberattacks. All this has motivated us to design and implement a new and advanced AC metamodel, named HEAD metamodel, that addresses the limitations of the existing metamodels--for example, generality, the hierarchy of components, dynamism, and extensibility of AC models--and works as a base to develop other essential features--for example policy migration, and collaboration and interoperability between AC models. The AC policy concerns what AC rules need to be enforced, while the AC mechanism concerns how AC rules are enforced. In this paper, we present two case studies inspired by ITMI's local (non-IoT) and IoT computing environments to show that our metamodel can be adapted to different computing environments, and various AC models can be instantiated with the needed components/attributes to fit the AC needs of an organization (or industry sector). For the AC policy, we apply the DSL grammar of HEAD metamodel to derive the needed model for each case study. We use Xtend notation to represent the concert instance of the derived model. The AC rules are generated as Cypher statements which are then injected into Neo4j to represent the NGAC policy as a graph. NGAC framework is used as an enforcement point for the rules generated for each case study. The results show that the HEAD metamodel:* Overcomes the limitations of the existing AC metamodels and can serve as a basis for other essential features. * Is a unified framework, and encompasses heterogeneous models. * Can be adapted into various local and distributed computing environments. * Can meet current AC requirements and follow policy upgrades. * Can generate different AC rules formats (e.g., Cypher statements, json...). Consequently, by applying the HEAD metamodel to the presented case studies, we demonstrate that it can be applied to more complex computing environments that include more users, machines, contexts, dynamic devices, and other variables. For example, highly dynamic IIoT environment with various static and dynamic AC rules. Moreover, the HEAD metamodel reveals some limitations of the NGAC framework. In theory, the NGAC graph includes obligations and prohibitions that express context and constraint elements, but in practice, they are not included. Hence, during implementation, this would make it difficult to make accurate access control decisions. As described in the case studies, we have to create multiple association relationships between UA nodes and OA nodes if some operations need to be performed without constraints by UA, and some other operations can be performed if some contextual (or non-contextual) constraints are true/false depending on the defined rule. Policies with minimum quality may lead to unacceptable situations and decisions, for example preventing users from accessing resources they are allowed to, or allowing some users to access resources they are not allowed to. As future perspectives, we aim to develop the needed methods to analyze and assess the obtained policies at run-time before enforcing them to avoid uncertainties concerning the obtained AC decision.