Research And Implementation Of Network Application Identification System

With the rapid development of the Internet, a variety of network applications appeared in our daily life including good and bad applications, due to the needs of the government, carriers, enterprises and other organizations. In order to allow network managers to keep controlling the status of the network and protect network uptime, network application identification and recognition system become a very important issue, which also has an important significance for network management and control.This thesis aims to the research and implementation of network application identification system, the main contents of the study consists of three parts, network application identification methods based on DPI; research and implementation of network application identification system; I-HASH multiple various position pattern matching algorithm in Internet application identification.This paper first introduces five common network applications, then we introduced the identification method combined with those five network application, given the several methods of network applications identification technology. Furthermore, this article focuses on the network application identification system, with the increasing number of network applications, the number of the characteristics’ rules in the existing network application identification system is expanding, resulting in system efficiency is low. On this basis, we have studied and improved identification system of the existing network applications, design and proposed a rule tree classification structure of the system initialization. The efficiency of multiple pattern matching is important to our network application identification system, for the fixed pattern fixed keyword in the rules, on the basis of the original sequence matching, this paper proposed a recursive hash multi-pattern matching algorithm. Experiments showed that with increase of the number of rules and packets, the time of the improved algorithm increases slowly, and greatly improved performance compared to the original algorithm.