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Graphical analysis of captured network packets for detection of suspicious network nodes

机译:图形化分析捕获的网络数据包以检测可疑的网络节点

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The advent of the Internet has yielded the rapid development of Information Technology related applications over the past two decades. Most organizations have adopted the use of a computer network to make accessibility and sharing of network applications and devices possible. However, currently, network security has been one of the critical things most organization and corporation has to handle. Each day, attacks are continually being executed into professional secured corporate or organization networks and sometimes into private networks. Wireshark is a tool generally used for network packet capture however, it is very tedious sometimes to filter and follow TCP streams. This problem exacerbates in a situation where colossal network data or traffic needs to be analyzed for suspicious traffic. This paper leverages the use of Python libraries and Data Science techniques to ease the packet capturing and graphical analysis process on a live network. Using these techniques will enhance the gleaning out more interesting attributes of network packet and fish out the suspicious IP address, network ports or malicious data readily within the shortest possible time. The research conducted showed how a broadcast IP address 255.255.255.255 might be suspicious within the internal network of the live university network. The suspicion was based on the payload data sent to this address and a possible error or misconfiguration on the Ubiquiti UniFi access point.
机译:互联网的出现在过去二十年中产生了信息技术相关应用的快速发展。大多数组织都采用了使用计算机网络来进行网络应用程序和设备的可访问性和共享。然而,目前,网络安全是大多数组织和公司都必须处理的重要事项之一。每天,攻击都不断被执行到专业的安全公司或组织网络中,有时是私人网络。 Wireshark是一般用于网络数据包捕获的工具,但有时会过滤和遵循TCP流非常繁琐。此问题在需要分析巨大网络数据或流量的情况下进行可疑流量的情况恶化。本文利用Python库和数据科学技术的使用来缓解实时网络上的数据包捕获和图形分析过程。使用这些技术将增强网络数据包的更有趣的属性,并在最短的时间内容易地捕获可疑IP地址,网络端口或恶意数据。进行的研究表明,在实况大学网络的内部网络中,如何可疑地进行广播IP地址255.255.255.255。疑似基于发送到此地址的有效载荷数据以及ubiquiti unifi接入点的可能错误或错误配置。

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