Federated Learning (FL) enables multiple users to collaboratively train a machine learning model without sharing raw data, making it suitable for privacy-sensitive applications. However, local model or weight updates can still leak sensitive information. Secure aggregation protocols mitigate this risk by ensuring that only the aggregated updates are revealed. Among these, single-setup secure aggregation protocols, where key generation and exchange occur only once, are the most efficient due to reduced communication and computation overhead. However, existing single-setup secure aggregation protocols often lack support for dynamic user participation and do not provide strong privacy guarantees such as forward and backward secrecy.

The digitisation of agriculture, integral to Agriculture 4.0, has brought significant benefits while simultaneously escalating cybersecurity risks. With the rapid adoption of smart farming technologies and infrastructure, the agricultural sector has become an attractive target for cyberattacks. This paper presents a systematic literature review that assesses the applicability of existing cyber threat intelligence (CTI) techniques within smart farming infrastructures (SFIs). We develop a comprehensive taxonomy of CTI techniques and sources, specifically tailored to the SFI context, addressing the unique cyber threat challenges in this domain. A crucial finding of our review is the identified need for a virtual Chief Information Security Officer (vCISO) in smart agriculture. While the concept of a vCISO is not yet established in the agricultural sector, our study highlights its potential significance. The implementation of a vCISO could play a pivotal role in enhancing cybersecurity measures by offering strategic guidance, developing robust security protocols, and facilitating real-time threat analysis and response strategies. This approach is critical for safeguarding the food supply chain against the evolving landscape of cyber threats. Our research underscores the importance of integrating a vCISO framework into smart farming practices as a vital step towards strengthening cybersecurity. This is essential for protecting the agriculture sector in the era of digital transformation, ensuring the resilience and sustainability of the food supply chain against emerging cyber risks.

Summary The literature on the challenges of and potential solutions to architecting cloud‐based systems is rapidly growing but is scattered. It is important to systematically analyze and synthesize the existing research on architecting cloud‐based software systems in order to build a cohesive body of knowledge of the reported challenges and solutions. We have systematically identified and reviewed 133 papers that report architecture‐related challenges and solutions for cloud‐based software systems. This paper reports the methodological details, findings, and implications of a systematic review that has enabled us to identify 44 unique categories of challenges and associated solutions for architecting cloud‐based software systems. We assert that the identified challenges and solutions classified into the categories form a body of knowledge that can be leveraged for designing or evaluating software architectures for cloud‐based systems. Our key conclusions are that a large number of primary studies focus on middleware services aimed at achieving scalability, performance, response time, and efficient resource optimization. Architecting cloud‐based systems presents unique challenges as the systems to be designed range from pervasive embedded systems and enterprise applications to smart devices with Internet of Things. We also conclude that there is a huge potential of research on architecting cloud‐based systems in areas related to green computing, energy efficient systems, mobile cloud computing, and Internet of Things. Copyright © 2016 John Wiley & Sons, Ltd.

Organizations involve in Global Software Development (GSD) face challenges in terms of having access to appropriate set of tools for performing distributed engineering and development activities, integration between heterogeneous desktop and web-based tools, management of artifacts developed and maintained over distant locations using different kind of tools, traceability among artifacts, and access to artifacts and data of sensitive nature. These challenges pose additional constraints on specific projects and reduce the possibility to carry out their engineering and development in globally distributed environment. In this paper, we argue the need to have a cloud-enabled platform for supporting GSD and propose reference architecture of a cloud based Platform for providing support to provision ecosystem of the Tools as a Service (PTaaS).

Cloud computing has gained significant attention of industry and academic sectors which are interested in adopting or experimenting with this technology. An increasing number of companies are expected to migrate their systems to cloud enabled infrastructures. However, there has not been much attention paid to provide sufficient process support. Since migration projects are likely to encounter several kinds of challenges, it is important to identify and share the process and logistical requirements of migration projects in order to build a body of knowledge of appropriate process, methods, and tools. This paper purports to contribute to the growing knowledge of how to migrate existing systems to cloud computing by reporting our effort aimed at migrating an Open Source Software (OSS) framework, Hackystat, to cloud computing. We report the main steps followed, the process and technical challenges faced, and some of the strategies that helped us to address those challenges. We expect the reported experiences can provide readers with useful insights into the process and technical aspects that should be considered when migrating existing software systems to cloud computing infrastructures.

Software evolution relates to how software systems evolve over time. With the emergence of the open source paradigm, researchers are provided with a wealth of data for open source software evolution analysis. In this paper, we present a systematic review of open source software (OSS) evolution. The objective of this review is to obtain an overview of the existing studies in open source software evolution, with the intention of achieving an understanding of how software evolvability (i.e., a software system's ability to easily accommodate changes) is addressed during development and evolution of open source software. The primary studies for this review were identified based on a pre-defined search strategy and a multi-step selection process. Based on their research topics, we have identified four main categories of themes: software trends and patterns, evolution process support, evolvability characteristics addressed in OSS evolution, and examining OSS at software architecture level. A comprehensive overview and synthesis of these categories and related studies is presented as well.