We present an approach for dynamically reconfiguring the role-based access control (RBAC) of information systems running business processes, to protect them against insider threats. The new approach uses business process execution traces and stochastic model checking to establish confidence intervals for key measurable attributes of user behaviour, and thus to identify and adaptively demote users who misuse their access permissions maliciously or accidentally. We implemented and evaluated the approach and its policy specification formalism for a real IT support business process, showing their ability to express and apply a broad range of self-adaptive RBAC policies.

The reengineering of systems into a microservice-based architecture can be seen as an implementation of a service-oriented architecture (SOA). However, the deployment of SOA into an enterprise is a challenging task, as it may involve the modernization of mission-critical systems with high technical debt and high maintenance costs. To this end, a process is required to provide an appropriate set of steps and techniques that minimize risks and at the same time ensure the quality of the systems during the migration process. Thus, this work presents the Service-oriented Process for Reengineering and DevOps—SPReaD, an instantiation of the mainstream SOA methodology focusing on the reengineering of legacy systems integrating DevOps aspects for developing microservices systems. This process has been defined during a real software reengineering project of legacy systems from a Brazilian State Department of Taxation. The results obtained include a substantial improvement in the quality of the main taxation system used by the state, including not only code-related metrics but also performance improvements of the services offered, and a change in the methodology adopted by the software development team.

Surrogate models provide virtual representations that mirror physical objects or processes, serving distinct purposes in simulations and digital transformation. This review article examines how integrating surrogate modelling with artificial intelligence (AI) techniques can facilitate the iterative development of surrogate models and identify instances where additional data acquisition is necessary to enhance the performance of a surrogate model. This demonstrates the potential of combining AI with surrogate modelling in addressing some of the key challenges in the food and drink manufacturing industry. The paper also provides an accessible examination of AI and surrogate modelling in the food and drink manufacturing industry, offering a summary of current applications and advancements within the field. The key areas addressed by this article include the application of AI and ML in process control, prediction, and modelling for food manufacturing, as well as the advantages and limitations of AI-based surrogate modelling (SM), among other issues addressed. Based on the literature reviewed herein, AI-based surrogate models can be employed to optimise production processes and reduce the need for extensive physical prototyping in the food and drink manufacturing industry. This review emphasises AI-based surrogate modelling techniques tailored for complex food processing systems and distinguishes itself by bridging method-specific insights with practical industrial relevance. Additionally, this article reviews challenges and limitations in the food and drink manufacturing industry and the application of surrogate modelling, along with future directions for research in this rapidly evolving field.

Distributed firewall systems emerged with the proposal of protecting individual hosts against attacks originating from inside the network. In these systems, firewall rules are centrally created, then distributed and enforced on all servers that compose the firewall, restricting which services will be available. However, this approach lacks protection against software vulnerabilities that can make network services vulnerable to attacks, since firewalls usually do not scan application protocols. In this sense, from the discovery of any vulnerability until the publication and application of patches there is an exposure window that should be reduced. In this context, this article presents Self-Adaptive Distributed Firewall (SADF). Our approach is based on monitoring hosts and using a vulnerability assessment system to detect vulnerable services, integrated with components capable of deciding and applying firewall rules on affected hosts In this way, SADF can respond to vulnerabilities discovered in these hosts, helping to mitigate the risk of exploiting the vulnerability. Our system was evaluated in the context of a simulated network environment, where the results achieved demonstrate its viability.

The self-adaptation of a software system is a complex process that depends on the system requirements, its operational state and environment, which may change during the system operational lifetime. Hence, the process for coordinating the self-adaptation should also be adaptable to changes that may occur during run-time. As a means for coordinating the self-adaptation process of software systems, the proposed approach employs workflows that are dynamically generated for dealing with the variability associated with the self-adaptation process. In this context, our aim is to define and develop techniques for automatically generate workflows for coordinating the self-adaptation of software systems. For demonstrating the feasibility of the proposed approach, architectural reconfiguration of software systems is used as an example, whereby the reconfiguration is managed by workflows that are dynamically generated depending on the availability of resources.