互联网环境下网络目标探测与获取技术研究

发布时间：2018-05-18 22:41

本文选题：目标探测 + 拓扑探测　；参考：《南京邮电大学》2014年硕士论文

【摘要】：随着网络规模日益扩大,网络安全问题日益凸显,网络攻击对用户使用及网络管理都造成了极大的影响。互联网环境下网络目标探测与获取技术作为网络攻防的基础,对其研究将有助于管理人员更好地了解自身网络安全状况,及时查漏补缺,防患于未然,同时其对于网络入侵检测也具有较好的应用价值和现实意义。本文在研究总结各类网络探测扫描技术,包括目标存活性探测、端口扫描、操作系统探测和网络拓扑探测的基础上,针对不同目标设计实现了对应探测获取方案。其中,对于单一主机这样一类简单目标,研究并实现了单一主机探测方案,主要包括目标存活性探测、端口扫描、操作系统探测等；对于包含大量主机的未知目标网络,首先设计一种分层聚类的单播网络拓扑推断方法来获取网络拓扑结构,在此基础上结合网络拓扑图,利用上述单一主机探测方案对目标网络的关键节点进行进一步的细粒度探测扫描,获取目标网络的重要信息。我们在C#下对单一目标探测获取方案进行了测试验证；而对于目标网络拓扑探测算法则基于NS-2平台进行仿真验证。实验结果表明：该算法能够在保证网络拓扑探测准确性的同时有效减少测量流量,提高了拓扑推断的效率。
[Abstract]:With the expansion of network scale, network security issues become increasingly prominent, and network attacks have a great impact on user use and network management. Network target detection and acquisition technology is the basis of network attack and defense under the Internet environment. The research on the technology will help managers to better understand their network security situation, check and fill the gaps in time, and prevent trouble in the future. At the same time, it has good application value and practical significance for network intrusion detection. Based on the research and summary of various network detection and scanning techniques, including target survivability detection, port scanning, operating system detection and network topology detection, this paper designs and implements corresponding detection acquisition schemes for different targets. For a simple target such as a single host, a single host detection scheme is studied and implemented, including target survivability detection, port scanning, operating system detection, etc. Firstly, a hierarchical clustering method of unicast network topology inference is designed to obtain the network topology. The single host detection scheme is used to scan the key nodes of the target network to obtain the important information of the target network. We test and verify the scheme of single target detection under C #, and simulate the algorithm of target network topology detection based on NS-2 platform. The experimental results show that the proposed algorithm can effectively reduce the measurement flow and improve the efficiency of topology inference while ensuring the accuracy of network topology detection.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.08

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