Abstract: Detecting insider threats is a task that analysts and information security administrators address in the commercial sector and in government organizations. Up to 75% of incidents involving insider actions are still detected manually. Detection of insider threats in an organization can be carried out using a set of organizational and technical measures. To identify them, the authors propose the use of behavioral and technical indicators. The aim of the article is to increase the effectiveness of countering random and malicious insider information security threats by developing a method for detecting insider activity in an organization. To achieve this goal authors used set-theoretic modeling, a hierarchy analysis method, a fuzzy logic apparatus and a fuzzy inference system. As a result of the study authors developed a method that allows detecting insider activity in an organization based on evaluating an employee's predisposition to insider activity and identifying an insider as a result of recording an information security incident. The developed method can be used to create an automated system for identifying insiders in an organization.