A company needs an AI capability to detect whether an IP address is coming from a suspicious source to protect its application from threats. Which solution type best meets this requirement?

An anomaly detection system is the most suitable solution because it identifies unusual patterns or outliers that deviate significantly from expected behavior. In this scenario, a "suspicious source" implies an IP address exhibiting abnormal characteristics compared to typical, benign traffic. The system learns what normal IP behavior looks like and flags anything outside that baseline as a potential threat. Speech recognition and named-entity recognition are natural language processing tasks unrelated to IP address analysis. While fraud forecasting involves predicting future fraudulent activities, anomaly detection is more direct for identifying currently suspicious sources based on real-time or near real-time data patterns, which aligns better with protecting an application from immediate threats.