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Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine learning techniques to flow statistical feature based classification methods. The nearest neighbor (NN)-based method has exhibited superior classification performance. It also has several important advantages, such as no requirements...
In order to share the knowledge of intrusion among distributed hosts and make the intrusion detect packages more efficient and reliable, a framework of distributed incremental intrusion detection based on SVM is proposed in the study. In this framework, the locate SVM detects the local attacks and take charge of collecting the new typical samples. A center SVM summarizes the distributed samples and...
Customer classification refers to a process in which customer information is divided into several sets of same characteristics by certain rules. According to different customer sets, we acquire different customer sets' behavior, and provide them with individual service. Thus customer's satisfaction and loyalty will be promoted highly. This paper employs BP neural networks to classify customer, and...
As a learning mechanic, support vector machine (SVMs) has been studied and applied in a wide area. This study deals with the special futures of SVM in predicting the total workload in telecommunication. The contributions include: (a) Building a predicted model of the total workload in telecommunications and predicting using it; (b)Analyzing the parameter of support vector regression(SVRs) which influence...
During recent years, distributed hash tables (DHTs) have been extensively studied by the networking community through simulation and analysis. Route table of each peer is the key component to ensure high performance and scalability for DHT network. Hence to measure peer's route table in real network is an important research topics for evaluation the performance and for understanding the structure...
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