A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source. Which solution meets these requirements?
A.
Build a speech recognition system.
B.
Create a natural language processing (NLP) named entity recognition system.
Anomaly detection systema can be used to identify patterns that deviate from the norm. This makes them ideal for analyzing incoming IP addresses and flag suspicious IPs based on traffic patterns.
Anomaly detection systema can be used to identify patterns that deviate from the norm. This makes them ideal for analyzing incoming IP addresses and flag suspicious IPs based on traffic patterns.
An anomaly detection system can analyze patterns and behaviors, such as IP address access patterns, to detect any deviations from the norm, which could indicate suspicious or malicious activity. An anomaly detection model can flag unusual access attempts, such as those from suspicious IP addresses, making it well-suited for threat detection.
Fraud forecasting (option D) typically focuses on predicting potential fraud patterns rather than real-time anomaly detection, so it would not directly address the need to check IP addresses for suspicious activity.
Thus, option C is the most suitable choice for identifying suspicious IP addresses in this scenario.
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