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This paper presents a Big Data-based approach to Network Security Situation Awareness (NS-SA) that utilizes machine learning and data purification techniques to enhance the accuracy and efficiency of network security monitoring. The proposed model, implemented using MATLAB and Python, addresses limitations of existing models by improving resource usage and applicability in real-time scenarios. Extensive testing demonstrates its potential in accurately assessing and forecasting network security conditions, o

Author

david9822

Language

EN