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Dynamical Network Forensics Based on Immune Agent

机译:基于免疫代理的动态网络取证

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Current network forensics systems are static and not real-time. In order to overcome the shortages, a dynamical network forensics model based on artificial immune theory and multi-agent theory, referred to as DNF, is introduced here. Comparing with traditional computer forensics methods, the new method provides the capacity that gathering real-time evidence dynamically as soon as network intrusions take place and saving the evidence in a safe way to prepare for the collection and analysis of the original evidence. In this paper, architecture of the model and the definitions of its components inspired by the immunity theory are given out. The experiment shows that it is able to insure the authenticity, integrality and validity of the digital evidence, and it is a new method for dynamic computer forensics.
机译:当前的网络取证系统是静态的,而不是实时的。为了克服这些不足,本文介绍了一种基于人工免疫理论和多主体理论的动态网络取证模型,简称为DNF。与传统的计算机取证方法相比,该新方法具有以下功能:一旦发生网络入侵,便可以动态地实时收集实时证据,并以安全的方式保存证据,以为原始证据的收集和分析做准备。在本文中,给出了该模型的体系结构以及受抗扰度理论启发的组成部分的定义。实验表明,该方法能够保证数字证据的真实性,完整性和有效性,是一种动态计算机取证的新方法。

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