Fuzzy Trust Modelling for Pervasive Computing Applications

Pervasive computing applications involve the interaction between autonomous entities for performing complex tasks and producing knowledge. Autonomous entities can interact to exchange data and knowledge to fulfil applications requirements. Intelligent Agents (IAs) ‘activated’ in various devices offer a lot of advantages when representing such entities due to their autonomous nature that enables them to perform the desired tasks in a distributed way. However, in such open and dynamic environments, IAs should be based on an efficient mechanism for trusting unknown entities when exchanging data. The trust level of an entity should be automatically calculated based on an efficient methodology. Each entity is uncertain for the characteristics and the intentions of the others. Fuzzy Logic (FL) seems to be the appropriate tool for handling such kind of uncertainty. In this paper, we present a model for trust calculation under the principles of FL. Our scheme takes into consideration the social dimension of trust as well as personal experiences of entities before they decide interactions with an IA. The proposed model is a two-level system involving three FL sub-systems to calculate (a) the social trust (based on experiences retrieved by the community), (b) the individual trust (based on personal experiences) and (c) the final trust. We present our results by evaluating the proposed system compared to other models and reveal its significance.

Internet-of-Things and Information Fusion: Trust Perspective Survey

The advent of Internet-of-Things (IoT) is creating an ecosystem of smart applications and services enabled by a multitude of sensors. The real value of these IoT smart applications comes from analyzing the information provided by these sensors. Information fusion improves information completeness/quality and, hence, enhances estimation about the state of things. Lack of trust and therefore, malicious activities renders the information fusion process and hence, IoT smart applications unreliable. Behavior-related issues associated with the data sources, such as trustworthiness, honesty, and accuracy, must be addressed before fully utilizing these smart applications. In this article, we argue that behavior trust modeling is indispensable to the success of information fusion and, hence, to smart applications. Unfortunately, the area is still in its infancy and needs further research to enhance information fusion. The aim of this article is to raise the awareness and the need of behavior trust modelling and its effect on information fusion. Moreover, this survey describes IoT architectures for modelling trust as well as classification of current IoT trust models. Finally, we discuss future directions towards trustworthy reliable fusion techniques.

Software Engineering Principles and Security Vulnerabilities

Software Engineering principles have connections with design science, including cybersecurity concerns pertaining to vulnerabilities, trust and reputation. The work of this paper surveys, identifies, establishes and explores these connections. Identification and addressing of security issues and concerns during the early phases of software development life cycle, especially during the requirements analysis and design phases; and importance of inclusion of security requirements have also been illustrated. In addition to that, effective and efficient strategies and techniques to prevent, mitigate and remediate security vulnerabilities by the application of the principles of trust modelling and design science research methodology have also been presented.