Network Security for Machine Learning
Comprehensive solutions for securing network infrastructure, traffic, and communications. Task: Machine LearningExplore 5 curated tools and resources
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A network detection and response platform that uses machine learning to analyze network metadata for threat detection without requiring hardware sensors or being affected by encryption.
A network detection and response platform that uses machine learning to analyze network metadata for threat detection without requiring hardware sensors or being affected by encryption.
A network detection and response solution that uses AI and machine learning to monitor network traffic, identify malicious behavior, and connect related security events to reveal attack patterns without requiring endpoint agents.
A network detection and response solution that uses AI and machine learning to monitor network traffic, identify malicious behavior, and connect related security events to reveal attack patterns without requiring endpoint agents.
NFStream is a multiplatform Python framework for network flow data analysis with a focus on speed and flexibility.
NFStream is a multiplatform Python framework for network flow data analysis with a focus on speed and flexibility.
ZAT is a Python package that processes and analyzes Zeek network security data using machine learning libraries like Pandas, scikit-learn, Kafka, and Spark.
ZAT is a Python package that processes and analyzes Zeek network security data using machine learning libraries like Pandas, scikit-learn, Kafka, and Spark.
Netcap efficiently converts network packets into structured audit records for machine learning algorithms, using Protocol Buffers for encoding.
Netcap efficiently converts network packets into structured audit records for machine learning algorithms, using Protocol Buffers for encoding.