The dawn of softwarized networks enables Network Slicing (NS) as an important technology
towards allocating end-to-end logical networks to facilitate diverse requirements of emerging …

Machine learning (ML) has become a core feature for today's real-world applications,
making it a trending topic for the software engineering community. Requirements …

The application of emerging technologies, such as Artificial Intelligence (AI), entails risks that
need to be addressed to ensure secure and trustworthy socio-technical infrastructures …

Today, many industrial processes are undergoing digital transformation, which often
requires the integration of well-understood domain models and state-of-the-art machine …

The rapid development of Machine Learning (ML) has demonstrated superior performance
in many areas, such as computer vision and video and speech recognition. It has now been …

We propose a security methodology for Machine Learning (ML) pipelines, supporting the
definition of key security properties of ML assets, the identification of threats to them as well …

This work considers challenges, related to the lack of methods of automatic threat modeling
and well-formed data sources of threats and countermeasures as well as techniques to …

Due to the proliferation of machine learning in various domains and applications, Machine
Learning Operations (MLOps) was created to improve efficiency and adaptability by …

Techniques and practices in RE are not well researched, although problems and the
research challenges on requirements engineering (RE) for machine learning-based systems …

The proper execution of requirements engineering processes can be decisive for the
success of software development and, for chatbots, it is no different. Chatbots have been …