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Detecting Malicious Domains by Massive DNS Traffic Data Analysis

机译:通过大量DNS流量数据分析检测恶意域

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DNS (Domain name System) is one of the most prevalent protocols on modern networks and is essential for the correct operation of many network activities including the malicious operation. Monitoring the DNS traffic is an effective method to detect malicious activities. In this paper, we proposed an approach to detect malicious domains by analyzing massive mobile web traffic data. We used multiple features to classify, including the textual features and the traffic statistics features of domains and presented three typical classifiers to compare the classifying effect of each. Spark framework is leveraged to speed up the calculation of a large-scale DNS traffic. The efficiency of our system makes us believe the approach can help a lot in the field of network security.
机译:DNS(域名系统)是现代网络上最流行的协议之一,对于许多网络活动(包括恶意操作)的正确运行至关重要。监视DNS流量是检测恶意活动的有效方法。在本文中,我们提出了一种通过分析海量移动Web流量数据来检测恶意域的方法。我们使用多种功能进行分类,包括域的文本功能和流量统计功能,并提出了三种典型的分类器来比较每种分类器的效果。利用Spark框架来加快大规模DNS流量的计算速度。我们系统的效率使我们相信该方法可以在网络安全领域提供很大帮助。

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