Gamification, the use of game design elements in applications that are not games, has been developed to provide attractive environments and maintain user interest in several domains. In domains such as education, marketing and health, where gamification techniques are applied, user engagement in applications has increased. In these applications the protection of users’ privacy is an important aspect to consider, due to the applications obtaining a record of the personal information of their users. Thus, the purpose of this paper is to identify if applications where gamification is applied do respect users’ privacy. For the accomplishment of this aim, two main steps have been implemented. Since the main principle of gamification is the existence of game elements, the first step was to identify the set of game elements recorded in the literature that are commonly applied in various applications. Afterwards, an examination of the relationship between these elements and privacy requirements was implemented in order to identify which elements conflict with the privacy requirements leading to potential privacy violations and which elements do not. Α conceptual model according to the results of this examination was designed, which presents how elements conflict with requirements. Based on the results, there are indeed game elements which can lead to privacy violations. The results of this work provide valuable guidance to software developers, especially during the design stages of gamified applications since it helps them to consider the protection of users’ privacy in parallel from the early stages of the application development onwards.

Migrating organisational services, data and application on the Cloud is an important strategic decision for organisations due to the large number of benefits introduced by the usage of cloud computing, such as cost reduction and on-demand resources. Despite, however, many benefits, there are challenges and risks for cloud adaption related to (amongst others) data leakage, insecure APIs and shared technology vulnerabilities. These challenges need to be understood and analysed in the context of an organisation’s security and privacy goals and relevant cloud computing deployment models. Although the literature provides a large number of references to works that consider cloud computing security issues, no work has been provided, to our knowledge, which supports the elicitation of security and privacy requirements and the selection of an appropriate cloud deployment model based on such requirements. This work contributes towards this gap. In particular, we propose a requirements engineering framework to support the elicitation of security and privacy requirements and the selection of an appropriate deployment model based on the elicited requirements. Our framework provides a modelling language that builds on concepts from requirements, security, privacy and cloud engineering, and a systematic process. We use a real case study, based on the Greek National Gazette, to demonstrate the applicability of our work.

In this paper certain interpretability criteria are taken into account in order to extract a set of linear inequality constraints for enhancing the fuzzy model interpretability. Among others, the criteria of model distinguishability, completeness, compactness, and fuzzy set sharing between rules are considered. To support distinguishability, the distances between fuzzy set centers are lower bounded, and the widths are manipulated as to control the overlap between fuzzy sets. Sufficient conditions are given to satisfy the completeness criterion, while the compactness requirement is addressed by comparing models with different number of rules. Finally, fuzzy set sharing between rules is achieved through a specialized procedure that involves fuzzy set merging. It turns out that the feasible region is a compact and convex set. The tradeoff between interpretability and accuracy is established by minimizing the model's square error over the feasible region through constrained particle swarm optimization. The method is tested using a number of high-dimensional data sets, and conducting two kinds of experiments. The first focuses on interpretability. The second studies the accuracy by comparing the method to other algorithms that perform unconstrained optimization, using nonparametric statistics.

Purpose: The purpose of this paper is to extend PriS (privacy safeguard), a privacy requirements engineering method for eliciting and modelling privacy requirements during system design, with the addition of privacy-aware cloud-based concepts to assist analysts to reason and model about privacy in cloud environments. Design/methodology/approach: An analysis of previous findings on the file of cloud privacy based on previous work has been conducted and a set of privacy-related concepts that need to be considered during privacy analysis for cloud-based systems have been revealed. These concepts were used for extending the conceptual model of PriS. Findings: The main finding of the paper is the design of a new, novel conceptual model that assists analysts and designers in reasoning about privacy in cloud environments. A new template using the JSON (Javascript notation object) format has been introduced for better expressing the privacy requirements along with the related concepts presented through the conceptual model, thus letting the developers to better understand the findings during the design stage and better guide them to the implementation of the respective solution. Research limitations/implications: The design of a cloud-based process that will guide analysts in detail for eliciting and modelling the identified privacy-related requirements is the limitation and in parallel the next step of the specific work presented here. Practical implications: The conceptual model has been applied on a real case scenario regarding its efficiency on capturing and mapping all necessary concepts for assisting analysts proceed with the design of the privacy-aware system. The results were positive, all concepts were easy to use and totally understandable from the design team and the stakeholders and the use of the JSON template received very positive comments, especially from the developer’s team. Originality/value: The paper presents a novel conceptual model for reasoning about privacy requirements in the cloud. The applicability of the proposed model has also been tested on a real case study.

As maritime and military missions become more and more complex and multifactorial over the years, there has been a high interest in the research and development of (autonomous) unmanned underwater vehicles (UUVs). Latest efforts concern the modeling and simulation of UUVs’ collaboration in swarm formations, towards obtaining deeper insights related to the critical issues of cybersecurity and interoperability. The research topics, which are constantly emerging in this domain, are closely related to the communication, interoperability, and secure operation of UUVs, as well as to the volume, velocity, variety, and veracity of data transmitted in low bit-rate due to the medium, i.e., the water. This paper reports on specific research topics in the domain of UUVs, emphasizing interoperability and cybersecurity in swarms of UUVs in a military/search-and-rescue setting. The goal of this work is two-fold: a) to review existing methods and tools of semantic modeling and simulation for cybersecurity and interoperability on the Internet of Underwater Things (IoUT), b) to highlight open issues and challenges, towards developing a novel simulation approach to effectively support critical and life-saving decision-making of commanders of military and search-and-rescue operations.