As enterprise networks grow more complex and cyber threats become increasingly sophisticated, traditional methods for network monitoring and security face significant limitations. To enhance the ability to detect unusual behaviors and analyze traffic effectively, organizations are increasingly leveraging machine learning algorithms for network anomaly detection and traffic analysis.

The Importance of Network Anomaly Detection and Traffic Analysis

Network anomaly detection involves identifying patterns in network traffic that deviate from the established norm. These anomalies often signal malicious activities such as cyberattacks, network intrusions, or operational failures. Traffic analysis complements this by providing a comprehensive view of data flows, bandwidth usage, and communication patterns within the network.

Together, these processes are vital for maintaining network security, performance, and reliability.

Role of Machine Learning in Network Security

Machine learning (ML) algorithms excel at uncovering hidden patterns from large volumes of data without explicit programming. In network security, ML models learn from … Read More