To adapt to the rapidly increasing vulnerabilities in software products and cyber threats that exploit them, security professionals are actively working with software developers to produce more secure systems. In software development, agile methods are increasingly adopted in critical software projects where security risks are prominent challenges. This adoption stems from the fact that agile methods are highly iterative and support delivering services and products in smaller batches which allows security professionals to seamlessly integrate software development security activities with agile methodologies. In addition, the iterative nature of agile software development encourages frequent inspections, tests, and patching of software systems to mitigate cybersecurity risks and vulnerabilities. Considering the massive growth of the Internet of Things (IoT) and Intelligent Transportation Systems (ITS) products, the challenge of software development while addressing the security and safety concerns of these devices will continue to increase. This paper presents a comprehensive and detailed review of agile software development in the context of IoT, ITS, and their cybersecurity and risk challenges. Furthermore, we provide a systematic comparison of the reviewed literature based on a set of defined criteria. Finally, we provide a broader outlook and an outline for designing future security-enhanced agile software development solutions for IoT and ITS systems.

Software systems in domains like Smart Cities, the Internet of Things or autonomous cars are coined by a high degree of distribution across several independent computing devices and the requirement to be able to adjust themselves to varying situations in their operational environment. Self-adaptive software systems are a natural choice to implement such context-dependent software systems. A multitude of approaches already implement self-adaptive systems and some consider even distribution aspects.Yet, none of the existing solutions supports the coordination of adaptation operations spanning multiple independent nodes, which is necessary to ensure a consistent adaptation even in presence of network errors or node failures. In this paper, we tackle this challenge to execute adaptations in distributed self-adaptive software systems in a coordinated manner. We present a protocol that enables the self-adaptive software system to execute correlated adaptations on multiple nodes in a transactional manner ensuring an atomic and consistent transition of the distributed system from its source to the desired target configuration. The protocol is validated to be free of deadlocks for any given adaptation at any point in time using a model-checking approach. The performance of our approach is investigated in experiments that emulate the protocol's execution on real devices for different sizes of distributed applications and adaptation scenarios.

<p dir="ltr">This thesis investigates nonlinear dynamical systems through a transdisciplinary lens, addressing three critical domains impacting human well-being: environmental pollution, climate migration and gender dynamics, and public health security. These are environmental induced challenges that impact health and social stability. These domains exhibit nonlinear characteristics that require adaptive, sustainable solutions beyond traditional linear approaches. Utilizing the Adaptive Pathways Framework (APF), this research integrates multi-scale fluid dynamics, engineering design, applied mathematics, and social science insights to create resilient models aligned with the United Nations Sustainable Development Goals (UNSDGs). The first focus area, aeroacoustic noise in urban air mobility, explores bio-inspired metamaterials for passive noise control. Periodic and quasi-periodic micropillar arrays inspired by sharkskin demonstrate significant noise reduction, contributing to quieter and more sustainable urban environments. The second area addresses climate migration, applying dimensional analysis from fluid dynamics to model migration patterns influenced by environmental, social, and economic factors. This framework offers policymakers quantitative tools for climate adaptation strategies. The third area centers on refugee empowerment, focusing on gender-targeted interventions that integrate STEM education and entrepreneurship to support social integration. This work provides scalable pathways for empowering refugee women and fostering resilience within refugee communities. The fourth area addresses gender equity in STEM, employing nudge theory and design thinking to challenge biases and create a more inclusive environment. Behavioral interventions here offer strategies for sustainable change in scientific research practices. Finally, the fifth area, public health security, explores sustainable innovations for pandemic resilience, including virus filtration and electrostatic disinfection technologies, balancing immediate health needs with long-term environmental considerations. This thesis underscores the efficacy of transdisciplinary approaches in tackling complex, nonlinear challenges, promoting sustainable, adaptive outcomes for global environmental, social, gender, and health stability.</p>