Proceedings ArticleDOI
Study on web DDOS attacks detection using multinomial classifier
Shital K. Ajagekar,Vaishali Jadhav +1 more
- pp 1-5
TLDR
This paper studied and discussed the algorithm of Naive Bayes Multinomial for testing and training, and the performance of this approach is compared with other existing classifiers into the terms of accuracy, true positive & false positive rates.Abstract:
Detecting DDoS attacks at application layer is quite challenging research problem. The recent methods are suffered from the poor accuracy performance of DDoS attack detection at application layer. In this paper, to mitigate current problems, classifier based system is proposed in which packets are captures, extraction of important fields those are required for detection and then apply classifier to detection of attack. In this paper, we studied and discussed the algorithm of Naive Bayes Multinomial for testing and training. The performance of this approach is compared with other existing classifiers into the terms of accuracy, true positive & false positive rates. The outcome of this paper is current method limitations and scope of improvement depicted from overall study and analysis. Additionally, the aim of this paper is to identify the research gap and limitations of studied method with review of previous methods.read more
Citations
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Journal ArticleDOI
Detection of reduction-of-quality DDoS attacks using Fuzzy Logic and machine learning algorithms
TL;DR: In this article, the use of four machine learning algorithms: Multi-Layer Perceptron (MLP) neural network with backpropagation, K-NN, Support Vector Machine (SVM) and Multinomial Naive Bayes (MNB) was used to detect low-rate DoS attacks.
Proceedings ArticleDOI
Classification and Optimization Scheme for Text Data using Machine Learning Naïve Bayes Classifier
Venkatesh,K. V. Ranjitha +1 more
TL;DR: A naïve bayes classifier which scales directly with number of indicators and data points which can be used for both binary and multiclass classification problems, and implemented using Machine Learning tool.
Book ChapterDOI
Optimization Scheme for Text Classification Using Machine Learning Naïve Bayes Classifier
TL;DR: A naive bayes classifier which scales directly with number of indicators and data points which can be used for both binary and multi-class classification problems, which demonstrates the performance improvement in the classification technique.
Proceedings ArticleDOI
Detection Methods of Slow Read DoS Using Full Packet Capture Data
TL;DR: This paper uses Full Packet Capture (FPC) datasets for detecting Slow Read DoS attacks with machine learning methods and demonstrates that FPC features are discriminative enough to detect such attacks.
Journal ArticleDOI
WEB DDoS Attack Detection Method Based on Semisupervised Learning
TL;DR: Wang et al. as discussed by the authors proposed a semisupervised learning detection model combining spectral clustering and random forest to detect the DDoS attack of the Web application layer and compared it with other existing detection schemes.