System and method for detection and prevention of computing device intrusion vectors using ai

Abstract

Systems, computer program products, and methods are described herein for detection and prevention of computing device intrusion vectors. The system utilizes an AI engine that employs natural language processing (NLP) to analyze incoming communications in real-time, identifying deviations from expected patterns based on user-specific and entity-specific behaviors. The system compares these communications against learned behaviors to detect anomalies indicative of potential intrusion attempts. Upon identifying such anomalies, the system assigns a priority level to the potential intrusion and initiates remediation actions, such as blocking suspicious communications or generating alerts. Additionally, the system continuously updates its AI model based on detected anomalies to improve future detection accuracy and provides user-specific training to enhance the user's ability to recognize potential hazards. This adaptive approach offers robust protection against evolving intrusion vectors, minimizing manual intervention and enhancing overall device security.