微型电脑应用

为了提高DoS攻击检测的准确率和降低误判率,针对ELM分类结果易受其初始输入权值和阈值的影响,提出了一种入侵杂草算法优化ELM的DoS攻击检测模型。选择DoS攻击检测的准确率为适应度,通过IWO优化ELM的初始输入权值和阈值,实现DoS攻击检测精度的提高。研究结果表明,与其他算法比较可知,IWO_ELM可以有效提高DoS攻击检测的准确率和降低误判率,为DoS攻击检测提供新的方法和途径。

In order to improve the accuracy of DoS attack detection and reduce the error detection rate, a DoS attack detection model with intrusion weed optimization algorithm was proposed for ELM classifications which are susceptible to the initial input weight and threshold. The accuracy of DoS attack detection is the adaptive degree, and the initial input weight and threshold of ELM are optimized by IWO to detect DoS attack. The results show that IWO_ELM can improve the accuracy of DOS attack detection and reduce the error detection rate.