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This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.

The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.

The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.

The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.

Despite the increasing interest in the metaverse—immersive three-dimensional virtual worlds wherein personalized avatars interact with one another—little is known about how users cognitively appraise and emotionally experience it. To fill this gap, the present study explores the emotional, behavioral and social consequences of users' cognitive appraisals, while focusing on social virtual reality (VR) as a representative entry point to the metaverse.

Drawing on cognitive appraisal theory against the backdrop of a framework for classifying emotions, this study develops and tests a theoretical model to account for users' continuance intention and its consequences in the social VR context based on two-wave panel survey data collected from 216 users of social VR platforms, including AltspaceVR, VRChat, Bigscreen and Rec Room.

The results of the first survey showed that perceived opportunity was more strongly influenced by technological opportunity than social opportunity, whereas perceived threat was more strongly affected by social threat than technological threat. Integrating the data collected from the first survey with those of the second survey, we also found that users' continuance intention positively influenced both their behavioral engagement and social self-efficacy.

By adopting a longitudinal approach, this study provides insights that may be valuable to researchers and practitioners who seek to use social VR for business purposes. This study also contributes to the metaverse literature by conceptualizing and operationalizing the opportunity and threat factors of social VR and identifying salient emotions that users experience in this context. Finally, this study has practical implications for addressing the social and technological features that may cause adverse user experiences in social VR.