A Model for User-centric Information Security Risk Assessment and Response
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Managing and assessing information security risks in organizations is a well understood and accepted approach, with literature providing a vast array of proposed tools, methods and techniques. They are, however, tailored for organizations, with little literature supporting how these can be achieved more generally for end-users, i.e. users, who are solely responsible for their devices, data and for making their own security decisions. To protect against them, technical countermeasures alone has been found insufficient as it can be misused by users and become vulnerable to various threats. This research focuses on better understanding of human behavior which is vital for ensuring an efficient information security environment. Motivated by the fact that different users react differently to the same stimuli, identifying the reasons behind variations in security behavior and why certain users could be “at risk” more than others is a step towards developing techniques that can enhance user’s behavior and protect them against security attacks. A user survey was undertaken to explore users security behavior in several domains and to investigate the correlation between users characteristics and their risk taking behavior. Analysis of the results demonstrated that user’s characteristics do play a significant role in affecting their security behavior risk levels. Based upon these findings, this study proposed a user-centric model that is intended to provide a comprehensive framework for assessing and communicating information security risks for users of the general public with the aim of monitoring, assessing and responding to user’s behavior in a continuous, individualized and timely manner. The proposed approach is built upon two components: assessing risks and communicating them. Aside from the traditional risk assessment formula, three risk estimation models are proposed: a user-centric, system-based and an aggregated model to create an individualized risk profile. As part of its novelty, both user-centric and behavioral-related factors are considered in the assessment. This resulted in an individualized and timely risk assessment in granular form. Aside from the traditional risk communication approach of one message/one-size-fits-all, a gradual response mechanism is proposed to individually and persuasively respond to risk and educate the user of his risk-taking behavior. Two experiments and a scenario-based simulation of users with varying user-centric factors has been implemented to simulate the proposed model, how it works and to evaluate its effectiveness and usefulness. The proposed approach worked in the way it was expected to. The analysis of the experiments results provided an indication that risk could be assessed differently for the same behavior based upon a number of user-centric and behavioral-related factors resulting in an individualized granular risk score/level. This granular risk assessment, away from high, medium and low, provided a more insightful evaluation of both risk and response. The analysis of results was also useful in demonstrating how risk is not the same for all users and how the proposed model is effective in adapting to differences between users offering a novel approach to assessing information security risks.
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