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Network Traffic Analysis for Real-Time Detection of Cyber Attacks

机译:网络流量分析,用于网络攻击的实时检测

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Preventing the cyberattacks has been a concern for any organization. In this research, the authors propose a novel method to detect cyberattacks by monitoring and analyzing the network traffic. It was observed that the various log files that are created in the server does not contain all the relevant traces to detect a cyberattack. Hence, the HTTP traffic to the web server was analyzed to detect any potential cyberattacks. To validate the research, a web server was simulated using the Opensource Damn Vulnerable Web Application (DVWA) and the cyberattacks were simulated as per the OWASP standards. A python program was scripted that captured the network traffic to the DVWA server. This traffic was analyzed in real-time by reading the various HTTP parameters viz., URLs, Get / Post methods and the dependencies. The results were found to be encouraging as all the simulated attacks in real-time could be successfully detected. This work can be used as a template by various organizations to prevent any insider threat by monitoring the internal HTTP traffic.
机译:防止网络攻击是任何组织的关注。在这项研究中,作者提出了一种通过监视和分析网络流量来检测网络内部的新方法。观察到,在服务器中创建的各种日志文件不包含检测网络内部的所有相关迹线。因此,分析了Web服务器的HTTP流量以检测任何潜在的网络ack。为了验证研究,使用OpenSource Damn易受攻击的Web应用程序(DVWA)模拟了一个Web服务器,并且根据OWASP标准进行了模拟了网络内容。 Python程序是脚本的脚本,捕获到DVWA服务器的网络流量。通过读取各种HTTP参数viz,实时分析此流量。,URL,get / post方法和依赖项。发现结果是令人鼓舞的,因为可以成功地检测到实时的所有模拟攻击。这项工作可以用作各种组织的模板,以防止任何内部HTTP流量来防止任何内幕威胁。

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