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Diagnosis of Distributed Denial of Service Attacks using the Combination Method of Fuzzy Neural Network and Evolutionary Algorithm

机译:模糊神经网络与进化算法相结合的分布式拒绝服务攻击诊断

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Availability, integrity and confidentiality are the key concepts of cyber security. Distributed denial of service attacks affecting the availability of information sources. This type of attack when be successful which led to the non-availability to the information sources. The success and impact of service denial attacks will be identified based on the victims and the risk level, threat and consequences of this attack, according to each case is different. The aim of this study is DDOS attack detection with differential evolutionary algorithm combination method and the fuzzy neural network ANFIS. For this purpose will pay to simulate and evaluate the proposed approach. In order to simulate in this research which is used MATLAB 2013b software which is a programming language and environment for scientific computing. The result of comparison showed that the ANFIS combination algorithm and differential evolution than to the ANFIS algorithm has more accuracy.
机译:可用性,完整性和机密性是网络安全的关键概念。分布式拒绝服务攻击会影响信息源的可用性。这种类型的攻击成功后会导致信息源不可用。服务拒绝攻击的成功和影响将根据受害者和攻击的风险程度,威胁和后果来确定,具体情况视情况而定。这项研究的目的是采用差分进化算法组合方法和模糊神经网络ANFIS进行DDOS攻击检测。为此,将需要模拟和评估所提出的方法。为了在本研究中进行仿真,使用了MATLAB 2013b软件,这是一种用于科学计算的编程语言和环境。比较结果表明,ANFIS组合算法和差分进化算法比ANFIS算法具有更高的准确性。

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