Denial of Service (DOS) attack is one of the most attack that attract the cyber criminals which aims to reduce the network performance from doing its intended functions. Moreover, DOS Attacks can cause a huge damage on the data Confidentiality, Integrity and Availability. This paper introduced a system that detects the network traffic and varies the DOS attacks from normal traffic based on an adopted dataset. The results had shown that the adopted algorithms with the ICMP variables achieved a high accuracy percentage with approximately 99.6 in detecting ICMP Echo attack, HTTP Flood Attack, and Slowloris attack. Moreover, the designed model succeeded with a rate of 100 in varying normal traffic from various DOS attacks.

翻译：拒绝服务攻击是网络犯罪分子最常采用的攻击手段之一，其目的是通过降低网络性能来阻碍系统正常执行预期功能。此外，拒绝服务攻击可能对数据的机密性、完整性和可用性造成严重损害。本文提出一种基于改进数据集的系统，通过监测网络流量并区分拒绝服务攻击与正常流量。实验结果表明，采用ICMP变量的算法在检测ICMP Echo攻击、HTTP洪水攻击和Slowloris攻击时取得了约99.6%的高准确率。此外，所设计的模型在区分正常流量与各类拒绝服务攻击方面达到了100%的识别率。