Machine Learning Algorithms for Threat Detection

Machine learning is at the core of AI-based threat detection, enabling systems to identify suspicious patterns and prevent cyberattacks. Key algorithms include:

• Supervised Learning: Models are trained using labeled datasets, allowing them to recognize predefined threats.
• Unsupervised Learning: Detects anomalies in network behavior by identifying patterns that deviate from the norm.
• Reinforcement Learning: AI learns optimal security strategies by continuously analyzing cyber threats and adapting to them.

By integrating these algorithms, threat detection systems can operate more efficiently with fewer false positives.