Performance Analysis of Linear Regression based Simple Reflex Artificial Intelligence Agent to Detect Malwares

The new pathogen detection method is developed using Linear Regression and Simple Reflex. This is accomplished using artificial intelligence. This straightforward yet efficient real-time detection method employs linear regression techniques to anticipate the presence of malware based on system activity patterns. The Simple Reflex AI agent responds to the system's current perceptions without considering prior data to facilitate rapid and precise detection. This method enhances the accuracy of detection and reduces the cost of computation. This is accomplished through the following steps: data collection, feature engineering, model training, and deployment. The model achieves a recall of 96.7%, an accuracy of 97.3%, a precision of 97.7%, and an F1-score of 96.9%, significantly outperforming signature-based detection methods. The results of this investigation indicate that linear regression enhances malware detection and is optimal for the identification of intricate maladies due to its robust and adaptable foundation.