Abstract
As organizations increasingly rely on digital technology to operate, protecting their information and data has become a critical concern. Information security systems are designed to safeguard digital assets against unauthorized access, use, disclosure, disruption, modification, or destruction. However, evaluating the effectiveness of an information security system can be challenging due to the complexity of the system and the diversity of threats it faces. In recent years, researchers have proposed using fuzzy inference to evaluate the effectiveness of information security systems. Fuzzy inference is a mathematical approach that can handle uncertain and imprecise information, making it well-suited for evaluating the effectiveness of information security systems. This research aims to develop a method for evaluating the effectiveness of an information security system based on fuzzy inference. The proposed method uses a set of performance indicators to measure the effectiveness of the system, such as the number of security incidents detected, the response time to security incidents, and the number of false positives and false negatives [1]. These indicators are then combined using fuzzy inference to generate an overall effectiveness score for the system. The proposed method will be evaluated using a real-world case study of an information security system deployed in an organization. The effectiveness score generated by the fuzzy inference method will be compared to the results obtained using traditional evaluation methods, such as the cost-benefit analysis or the return-on-investment analysis. The results of the study will demonstrate the effectiveness and usefulness of the proposed method for evaluating information security systems.