Signature-based detection compares signatures against which of the following?

Signature-based detection is a critical concept in network security and refers to the method of identifying malicious activity by comparing observed data or traffic against a database of known signatures or patterns of known threats. This approach relies heavily on the existence of predefined patterns that have been identified through previous threat analysis.

When a system uses signature-based detection, it scans the incoming and outgoing data for specific patterns that match those contained in its signature database. If a match is found, it indicates a potential security threat, such as a virus, worm, or other types of malware. This method is effective because it can quickly identify known threats based on their unique byte sequences or behaviors.

Known patterns are indeed what the signatures represent, but they are not the focal point of the comparison. Instead, the focus is on the real-time data that is actively observed on the network. This real-time observation allows for immediate action against threats, making it a crucial approach in cybersecurity practices.

In contrast, scheduled events, observed events, and temporary logs may not provide the precise mechanism of matching known threat signatures to current data flows. Signature-based detection specifically targets active data to ensure prompt detection and response to potential threats based on prior knowledge of those threats.