How does an anomaly based scanner identify potential malware infections?

An anomaly-based scanner identifies potential malware infections by monitoring for unusual resource consumption. This method involves establishing a baseline of normal behavior within a system. It observes the usual patterns of data flow, CPU usage, memory consumption, and other operational metrics. When the scanner detects behavior that deviates significantly from this established baseline, it flags it as a potential threat. Such anomalies can include unexpected spikes in CPU usage, strange network traffic patterns, or unusual file modifications, which are common indicators of malware activity.

This technique is particularly effective because it does not rely on prior knowledge of specific malware signatures. Instead, it can potentially detect new or unknown malware strains that have not yet been cataloged. This proactive approach allows for the identification of threats that traditional signature-based methods might miss since those rely on previously identified malware signatures.

In contrast, the other methods mentioned, such as matching file signatures or checking user permissions, focus on known vulnerabilities or conditions rather than spotting unusual activities indicative of malware. Disabling other scanning software does not directly relate to identifying threats but rather affects the overall security posture of the system. Therefore, the focus on identifying deviations from normal activity underscores the strength of the anomaly-based scanner in detecting potential malware infections.