高抽象度網(wǎng)絡(luò)模擬方法研究及其應(yīng)用
[Abstract]:Network simulation is one of the most important methods to study network activities and behaviors, and has high academic research and application value. With the development of computer technology and the expansion of network scale, the research of network simulation method and its related applications have put forward higher requirements and goals. On the one hand, how to reduce the complexity of network topology in the simulation of complex networks, that is, to reduce the computational overhead, reduce the simulation time, and fully guarantee the authenticity of simulation, is the key problem to be solved in the research of network simulation methods. On the other hand, how to study security applications, such as intrusion detection system, based on high abstraction network simulation method, is another important problem in this paper. Therefore, taking the theoretical research of network simulation as the starting point, this paper makes a deep research on the method of high abstraction network simulation, analyses and verifies it through experiments, aiming at reconciling the contradiction between "complexity" and "authenticity" in network simulation. The theoretical research is raised to the application level. Based on the high abstraction network simulation method, the application of network security is studied, deeply studied, optimized, the detection model in intrusion detection system is improved, and the attack detection simulation experiment is carried out. Specifically, the main contents of this paper include the following three aspects: 1) A new high abstract network simulation method is proposed, that is, topologically focused network traffic simulation method. The main idea of this method is to divide the network topology into focus area FTA (Focusing Topology Area) and unfocused area NFTA (Non-Focusing Topology Area), divides the data packet into three types according to the difference of the area in which the data packet is in the network traffic). Different simulation strategies and algorithms are adopted for different types of packets. The simulation results of complex networks show that the proposed method can reduce the complexity of the network, reduce the computational overhead and ensure the simulation authenticity of the focus region. Especially, the authenticity of data packets in network traffic. 2) A security application research framework based on high abstract network simulation is proposed. Based on network simulation experiment platform, the detection model in intrusion detection system (IDS) is studied. On the basis of the existing intrusion detection model based on classical DS (Dempster-Shafer) evidence theory, the concept of weight value is introduced, and an optimized DS evidence theory, ODS evidence theory (Optimized DS evidence theory), is proposed. Combined with the basic probability assignment function (RBPA (Regression Basic Probability Assignment function),) with regression ability, a new network intrusion detection model, ODS RBPA model, is proposed. 3) the network simulation technology and method are used. A large-scale and complex network environment with multiple intrusion attacks is simulated. The performance and effectiveness of the ODS RBPA intrusion detection model are verified in this simulated network environment. By comparing with the results of multi-group simulation experiments of other detection models, it is verified that the new detection model not only has high detection rate, low false alarm rate and strong stability, but also has a strong ability to detect unknown attacks.
【學(xué)位授予單位】:江南大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2016
【分類號】:TP393.08
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