Network Traffic Analysis using Big Data and Deep Learning Techniques

Alaeddine Boukhalfa, Abderrahim Abdellaoui, N. Hmina, H. Chaoui
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引用次数: 2

Abstract

Today the world is experiencing a rapid revolution in the field of information technology, several apparatus and devices generate data and exchange them through the network, these exchanges are not generally secured, they may contain hidden new attacks and intrusions undetectable by the existing tools of security. In addition, the increasing volume and the variety of data of these exchanges make the detection of the menaces more difficult. To solve these problems, we propose in this paper, a new idea of network traffic analysis based on gathering large data of traffic of the network using Big Data frameworks, and analyzing it with Deep Learning techniques in order to identify new invisible threats.
使用大数据和深度学习技术的网络流量分析
当今世界正在经历信息技术领域的快速革命,许多仪器和设备产生数据并通过网络交换数据,这些交换通常不安全,它们可能隐藏着现有安全工具无法检测到的新攻击和入侵。此外,这些交换的数据量和种类的增加使得检测威胁变得更加困难。为了解决这些问题,本文提出了一种新的网络流量分析思路,即利用大数据框架收集网络流量的大数据,并利用深度学习技术对其进行分析,以识别新的无形威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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