Behavior-based Detection
Behavior-based detection is a technique used in data science and artificial intelligence to identify anomalies or threats by analyzing the behavior of entities such as users, devices, or applications. This approach involves creating a baseline of normal behavior and then monitoring for deviations from that baseline. The baseline is established by analyzing historical data and identifying patterns of behavior that are considered normal. Once the baseline is established, any deviation from it is flagged as a potential threat or anomaly. Behavior-based detection is commonly used in cybersecurity to detect and prevent attacks such as malware infections, phishing attempts, and data exfiltration. It is also used in fraud detection, network monitoring, and system performance analysis.
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