Bridging the Gap Between Learning and Security: An Investigation of Blended Learning Systems and Ransomware Detection

Blended learning has been identified as a potentially viable strategy for enhancing the efficacy and efficiency of online learning through the integration of conventional instructional approaches. Despite the potential advantages, educational institutions have exhibited reluctance in embracing this strategy due to a range of difficulties. A prominent issue of concern pertains to the escalating menace posed by Ransomware virus assaults, which have the potential to result in substantial financial ramifications and reputational harm. This study aims to examine the many elements that impact student satisfaction in utilising blended learning systems, focusing primarily on the modules, channels, and lecturers involved. This evaluation seeks to improve students' comprehension of literacy within the context of classroom discourses. In addition, our study aims to enhance the precision of Ransomware detection by examining the intricate characteristics of the malicious software, particularly by analysing assembly language instruction patterns. The N-gram technique is employed in a two-stage process for feature extraction. This procedure involves the computation of pattern statistics and subsequent feature selection to effectively reduce dimensionality. In order to assess the efficacy of the chosen features, we employ a feature cataloguing methodology with the Random Forest algorithm, utilising the lowest out-of-bag (OOB) error and a predetermined number of trees. Our experiments showcase that this method achieved the highest accuracy, sensitivity value, false positive rate, and precision. On its whole, our study presents a thorough methodology for improving student happiness and virus detection accuracy inside blended learning systems. Through the use of our research outcomes, educational establishments have the potential to furnish pupils with a learning encounter that is both captivating and efficacious, while concurrently minimising the vulnerabilities associated with cyber-attacks.