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With the widespread adoption of data centers and cloud computing technologies, the volume and complexity of network attacks have grown significantly. While traditional security mechanisms, such as firewalls and intrusion detection systems, can filter some attack traffic effectively, they face the following limitations when dealing with complex attacks:
1. Static rules cannot address the dynamic nature of evolving attack behaviors.
2. They fail to capture and analyze novel attack behaviors promptly.
3. A lack of flexibility in resource allocation results in inefficiencies.
Our proposed solution leverages the flexible traffic management capabilities of SDN technology combined with the efficient data analysis and predictive capabilities of AI models. This approach enables adaptive responses to attack behaviors, enhancing network defense capabilities while significantly reducing resource costs.
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IEEE/ICACT20250010 Slide.04
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