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Security models have been designed to ensure data is accessed and used in proper manner according to the security policies. Unfortunately, human role in designing security models has been ignored. Human behavior relates to many security breaches and plays a significant part in many security situations. In this paper, we study users' decision-making toward security and usability through the mental model approach. To elicit and depict users' security and usability mental models, crowd sourcing techniques and a cognitive map method are applied and we have performed an experiment to evaluate our findings using Amazon MTurk.

The goal of this study is to categorize stakeholders in Internet of Things (IoT) security based on their roles in order to address the challenges associated with managing the large amount of data generated by IoT devices. With the increasing number of connected devices, the security risks also escalate, necessitating skilled stakeholders to mitigate these risks and prevent potential attacks. This study proposes a two-part approach that involves clustering stakeholders according to their responsibilities and determining relevant features to enhance decision-making. By grouping stakeholders into shared categories, the study aims to provide a more efficient and effective method for managing IoT security. The insights gained from this research will not only benefit stakeholders involved in IoT security but also assist policymakers and regulators in developing effective strategies.

This study aims to address the challenges of managing the vast amount of data generated by Internet of Things (IoT) devices by categorizing stakeholders based on their roles in IoT security. As the number of connected devices increases, so do the associated security risks, highlighting the need for skilled stakeholders to mitigate these risks and prevent potential attacks. The study proposes a two-part approach, which involves clustering stakeholders according to their responsibilities and identifying relevant features. The main contribution of this research lies in enhancing decision-making processes within IoT security management. The proposed stakeholder categorization provides valuable insights into the diverse roles and responsibilities of stakeholders in IoT ecosystems, enabling a better understanding of their interrelationships. This categorization facilitates more effective decision making by considering the specific context and responsibilities of each stakeholder group. Additionally, the study introduces the concept of weighted decision making, incorporating factors such as role and importance. This approach enhances the decision-making process, enabling stakeholders to make more informed and context-aware decisions in the realm of IoT security management. The insights gained from this research have far-reaching implications. Not only will they benefit stakeholders involved in IoT security, but they will also assist policymakers and regulators in developing effective strategies to address the evolving challenges of IoT security.

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