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Research and Application of APT Attack Defense and Detection Technology Based on Big Data Technology

机译:基于大数据技术的APT攻击防御与检测技术的研究与应用

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In order to excavate security threats in power grid by making full use of heterogeneous data sources in power information system, this paper proposes APT (Advanced Persistent Threat) attack detection sandbox technology and active defense system based on big data analysis technology. First, the file is restored from the mirror traffic and executed statically. Then, sandbox execution was carried out to introduce analysis samples into controllable virtual environment, and dynamic analysis and operation samples were conducted. Through analyzing the dynamic processing process of samples, various known and unknown malicious code, APT attacks, high-risk Trojan horses and other network security risks were comprehensively detected. Finally, the threat assessment of malicious samples is carried out and visualized through the big data platform. The results show that the method proposed in this paper can effectively warn of unknown threats, improve the security level of system data, have a certain active defense ability. And it can effectively improve the speed and accuracy of power information system security situation prediction.
机译:为了充分利用电力信息系统中异构数据源来挖掘电网安全威胁,提出了基于大数据分析技术的APT(Advanced Persistent Threat)攻击检测沙箱技术和主动防御系统。首先,从镜像流量还原文件并静态执行。然后,执行沙箱操作以将分析样本引入可控的虚拟环境中,并进行动态分析和操作样本。通过分析样本的动态处理过程,全面检测出各种已知和未知的恶意代码,APT攻击,高风险特洛伊木马和其他网络安全风险。最后,通过大数据平台对恶意样本进行威胁评估并可视化。结果表明,本文提出的方法可以有效地警告未知威胁,提高系统数据的安全水平,具有一定的主动防御能力。可以有效提高电力信息系统安全态势预测的速度和准确性。

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