Program-Linked Operation Remediation with Stateful Live Malware Detection

The patent segments the monitoring task by focusing on specific system calls and operations rather than monitoring all process behaviors. It divides the complex monitoring function into targeted observation of critical operations (file access, registry modifications, network connections) which reduces complexity while maintaining effective malware detection.

The patent employs preliminary action by establishing a baseline of normal system operations and creating a stateful model before malware infection occurs. This allows the system to detect deviations from normal behavior without requiring continuous complex analysis of all process behaviors, reducing monitoring overhead while maintaining detection reliability.

The patent applies local quality by monitoring only specific critical operations and system calls that are most indicative of malware behavior, rather than monitoring all process operations uniformly. This selective monitoring approach maintains high detection accuracy for malicious activities while significantly reducing resource consumption compared to comprehensive monitoring.

The system uses the operating system's own event logging and process tracking mechanisms to monitor malware behavior, rather than implementing a separate comprehensive monitoring system. This self-service approach leverages existing system resources and reduces additional resource consumption while maintaining detection accuracy.

The patent implements feedback mechanisms where the system continuously monitors process behaviors, compares them against established baselines and stateful models, and adjusts monitoring intensity or response actions accordingly. This feedback loop allows real-time detection while maintaining system stability by adapting to normal system variations and only intervening when genuine anomalies are detected.

The monitoring system dynamically adjusts its behavior based on the operational context, transitioning between passive monitoring and active remediation modes. This dynamic approach enables real-time response to malware while preserving system stability during normal operation, as the system only intervenes when necessary based on detected anomalies.

The patent merges signature-based detection with behavior-based monitoring in a hybrid approach. It combines the speed of signature matching with the adaptability of behavior analysis by monitoring process operations and comparing them against stateful models, enabling both fast detection of known malware and effective detection of modified variants.

The system implements a multi-functional detection mechanism that can operate in multiple modes: signature-based for known malware, behavior-based for unknown variants, and stateful modeling for contextual analysis. This universality allows the system to maintain detection speed for familiar patterns while adapting to modified and obfuscated malware through behavioral analysis.