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A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks

机译：基于决策树和自适应多层神经网络的P2P僵尸网络检测方案

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Mohammad Alauthaman; Nauman Aslam; Li Zhang; Rafe Alasem; M. A. Hossain;
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年度 2016
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1. 基于网络行为特征与Dezert-Smarandache理论的P2P僵尸网络检测 [J] . 宋元章, 陈媛, 王俊杰, 东南大学学报（英文版） . 2018,第002期
2. A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks [J] . Alauthaman Mohammad, Aslam Nauman, Zhang Li, Neural computing & applications . 2018,第11期

机译：基于决策树和自适应多层神经网络的P2P僵尸网络检测方案
3. Botnet detection used fast-flux technique, based on adaptive dynamic evolving spiking neural network algorithm [J] . Ammar Almomani, Ahmad Al-Nawasrah, Mohammad Alauthman, International journal of ad hoc and ubiquitous computing . 2021,第1期

机译：僵尸网络检测使用快速通量技术，基于自适应动态演化尖刺神经网络算法
4. A Two-Stream Network Based on Capsule Networks and Sliced Recurrent Neural Networks for DGA Botnet Detection [J] . Xinjun Pei, Shengwei Tian, Long Yu, Journal of network and systems management . 2020,第4期

机译：基于胶囊网络的双流网络，切片经常性神经网络用于DGA僵尸网络检测
5. HTTP Botnet Detection Using Adaptive Learning Rate Multilayer Feed-Forward Neural Network [C] . G. Kirubavathi Venkatesh, R. Anitha Nadarajan IFIP WG 11.2 International workshop on information security theory and practice . 2012

机译：使用自适应学习速率多层前馈神经网络的HTTP僵尸网络检测
6. Detection of rare events and rule extraction by neural networks and decision trees. [D] . Choe, Wooyoung. 1999

机译：通过神经网络和决策树检测稀有事件并提取规则。
7. A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks [O] . Mohammad Alauthaman, Nauman Aslam, Li Zhang, -1

机译：基于决策树和自适应多层神经网络的P2P僵尸网络检测方案
8. A P2P Botnet Detection Scheme based on Decision Tree and Adaptive Multi-layer Neural Networks [O] . Alauthman Mohammad, Aslam Nauman, Zhang Li, 2016

机译：基于决策树和自适应多层神经网络的P2P僵尸网络检测方案
9. AGNO: An Adaptive Group Communication Scheme for Unstructured P2P Networks [R] . Tsoumakos, D. , Roussopoulos, N. 2004

机译：aGNO：非结构化p2p网络的自适应群组通信方案

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks

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