The technology of cloud computing is becoming more dynamic every day. Providing IT services to academic institutions and other commercial businesses has many advantages. The cloud-based Learning Management System (LMS) has been increasingly used in Comprehensive Universities in developing countries. Lecturers are able to post lesson plans, homework assignments, and exams on the cloud server, which gives students access to all the course materials from home or at university. As noticeable, cloud providers face a variety of security challenges such as risks, threats and vulnerabilities. A cloud provider in an academic institution needs to understand and reduce cloud security risks, improve security and increase confidence in cloud services. Thus, a risk management model is essential for securing cloud-based LMS in academic institutions. This paper proposes a risk management model based on fuzzy rule-based logic for mitigation of security concerns in risks for cloud-based LMS in academic institutions. It identifies and characterizes the critical risk factors associated with insider threats prevalent in a cloud-based LMS environment. It presents the process of collecting and preprocessing log data from server logs and Moodle application logs to extract relevant features indicative of these security risks. It creates a model based on fuzzy rules to evaluate and measure the risk levels. The output of this model is a risk level that provides a nuanced assessment of the security posture of the cloud-based LMS.This proposed model seeks to improve educational institutions’ cloud cybersecurity posture by fortifying LMS platforms’ security resistance against insider threats.