Journal ArticleDOI
The hybrid technique for DDoS detection with supervised learning algorithms
Soodeh Hosseini,Mehrdad Azizi +1 more
TLDR
A novel hybrid framework based on data stream approach for detecting DDoS attack with incremental learning is proposed and the naive Bayes, random forest, decision tree, multilayer perceptron (MLP), and k-nearest neighbors (K-NN) on the proxy side to make better results.About:
This article is published in Computer Networks.The article was published on 2019-07-20. It has received 74 citations till now. The article focuses on the topics: Multilayer perceptron & Attack model.read more
Citations
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Journal ArticleDOI
A dynamic MLP-based DDoS attack detection method using feature selection and feedback
Meng Wang,Lu Yiqin,Qin Jiancheng +2 more
TL;DR: This paper combined sequential feature selection with MLP to select the optimal features during the training phase and designed a feedback mechanism to reconstruct the detector when perceiving considerable detection errors dynamically.
Journal ArticleDOI
Detection of DDoS attacks with feed forward based deep neural network model
TL;DR: The experiments carried out on the CICDDoS2019 dataset containing the current DDoS attack types created in 2019 showed that the attacks on network traffic were detected with 99.99% success and the attack types were classified with an accuracy rate of 94.57%.
Journal ArticleDOI
An efficient and robust deep learning based network anomaly detection against distributed denial of service attacks
TL;DR: AE-SVM trained with CICIDS successfully captures virtually generated DDOS traffic data and contributed to the solution of the high false-positive problem compared to other models.
Journal ArticleDOI
Detection of distributed denial of service attack in cloud computing using the optimization-based deep networks
TL;DR: Cloud computing services provide a wide range of resource pool for maintaining a large amount of data as mentioned in this paper and are commonly used as the private or public data forum based on the demand, and...
Journal ArticleDOI
A feature reduction based reflected and exploited DDoS attacks detection system
Deepak Kshirsagar,Sandeep Kumar +1 more
TL;DR: This study presents a DDoS attack detection framework to detect reflection and exploitation based DDoS attacks in an efficient manner and proposes a feature reduction method by the combination of information gain and correlation feature selection techniques.
References
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Data Mining: Practical Machine Learning Tools and Techniques
TL;DR: This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
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Min Chen,Shiwen Mao,Yunhao Liu +2 more
TL;DR: The background and state-of-the-art of big data are reviewed, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid, as well as related technologies.
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A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
TL;DR: The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.
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A dynamic MLP-based DDoS attack detection method using feature selection and feedback
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