Wireless Sensor Network (WSN) has been widely used in many important areas. MAC protocols have a significant effect on the function of WSN. This paper introduced various important MAC protocols, analyzed the fundamental mechanism of each MAC protocol in details,and compared the characteristics and performances of each MAC protocol. Finally, the future research strategies and trends of MAC protocols in WSN are summarized.
The modeling of network intrusion detection is a kind of significant network security protection technology. Nowadays, the network intrusion detection model can not accurately describe the intrusion behavior, so that incomplete network intrusion detection will occur. Therefore, based on machine learning algorithm, a network intrusion detection model is designed in the paper, which supports the fact that vector machine (SVM) fits the mapping relationship between network intrusion detection characteristics and network intrusion behavior. Meanwhile, a network intrusion detection model that reflects the relationship between the two aspects is established in the paper too. As a result, the experimental results show that the model proposed in the paper can not only accurately identify the network intrusion behavior, but has a very fast detection speed. Moreover, the model proposed in the paper has obtained much better network intrusion detection results than that of other models, which is of wide application prospect.
The modeling of network intrusion detection is an important network security protection technology. The current network intrusion detection model can not accurately describe the intrusion behavior, resulting in incomplete network intrusion detection. Therefore, a network intrusion detection model based on machine learning algorithm was designed. In addition, support vector machine (SVM) fits the mapping relationship between network intrusion detection characteristics and network intrusion behavior, and established a network intrusion detection model that reflected the relationship between the two aspects. Finally, the experimental results showed that the model not only can accurately identify the network intrusion behavior, but also has a very fast detection speed. It has obtained better network intrusion detection results than other models, and had a wide application prospect. I. INTRODUCTION Network security is an important aspect in cyberspace security. The security of network infrastructure provides the basis for the reliable operation of the Internet. And various network security detection measures provide secure communications for the development of various Internet activities. Machine learning technology has a wide range of applications in BGP anomaly detection, malicious domain name detection, botnet detection, network intrusion detection,and malicious encrypted traffic identification.Domain name system is one of the core applications in the Internet. It often becomes the target of attack, or is used by attackers as an attack tool. Therefore, the security of the domain name system has always been the research focus of network security. The early malicious domain name detection method was to set a malicious domain name blacklist or an interception list in the domain name system, firewall or network intrusion detection system. This method can easily be evaded detection by attackers. The followed method based on inquiry number has problems of high
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