Introduction of a Trusted Whitelist Mechanism for DDOS Attack Early Warning Optimization

Distributed Denial of Service (DDoS) attacks pose a significant threat to modern networks, leading to substantial computational resource consumption and economic losses. Many mature defense technologies exist to block malicious traffic and deploy honeypots for traffic monitoring, enabling early detection and mitigation of attacks. However, these defenses can disrupt normal client services, especially during peak network usage, due to over-blocking and inaccurate attack situation assessments. This paper introduces an optimized mechanism involving a trusted whitelist, which filters legitimate clients in advance during the DDoS attack Early warning stage, addressing potential misjudgments during peak network times. Experimental results show that this mechanism can more effectively and accurately discern DDoS situations, reducing the likelihood of false positives.