.png){kind=icon}
返回
Application Layer DDoS Attack Detection Using Cuckoo Search Algorithm-Trained Radial Basis Function
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2022.3182818.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In an application-layer distributed denial of service (App-DDoS) attack, zombie computers bring down the victim server with valid requests. Intrusion detection systems (IDS) cannot identify these requests since they have legal forms of standard TCP connections. Researchers have suggested several techniques for detecting App-DDoS traffic. There is, however, no clear distinction between legitimate and attack traffic. In this paper, we go a step further and propose a Machine Learning (ML) solution by combining the Radial Basis Function (RBF) neural network with the cuckoo search algorithm to detect App-DDoS traffic. We begin by collecting training data and cleaning them, then applying data normalizing and finding an optimal subset of features using the Genetic Algorithm (GA). Next, an RBF neural network is trained by the optimal subset of features and the optimizer algorithm of cuckoo search. Finally, we compare our proposed technique to the well-known k-nearest neighbor (k-NN), Bootstrap Aggregation (Bagging), Support Vector Machine (SVM), Multi-layer Perceptron) MLP, and (Recurrent Neural Network) RNN methods. Our technique outperforms previous standard and well-known ML techniques as it has the lowest error rate according to error metrics. Moreover, according to standard performance metrics, the results of the experiments demonstrate that our proposed technique detects App-DDoS traffic more accurately than previous techniques.
Keyword:
Servers
Feature extraction
Genetic algorithms
Denial-of-service attack
Support vector machines
Computer crime
Load modeling
Application layer DDoS
machine learning
radial basis function
cuckoo search algorithm
genetic algorithm
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
分享收藏An Effective Probabilistic Technique for DDoS Detection in OpenFlow ControllerOpenFlow控制器中有效的DDoS检测概率技术
PREAI
分享收藏A Machine Learning-Based Classification and Prediction Technique for DDoS Attacks一种基于机器学习的DDoS攻击分类预测技术.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏分享收藏SDN-Based Architecture for Transport and Application Layer DDoS Attack Detection by Using Machine and Deep LearningIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容