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Network-based Intrusion Detection ―Modeling for a Larger Picture

机译:基于网络的入侵检测―建模更大的图片

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摘要

The Internet is changing computing more than ever before. As the possibilities and the scopes are limitless, so too are the risks and chances of malicious intrusions. Due to the increased connectivity and the vast spectrum of financial possibilities, more and more systems are subject to attack by intruders. One of the commonly used method for intrusion detection is based on anomaly. Network based attacks may occur at various levels, from application to link levels. So the number of potential attackers or intruders are extremely large and thus it is almost impossible to "profile" entities and detect intrusions based on anomalies in host-based profiles. Based on meta-information, logical groupings has been made for the alerts that belongs to same logical network, to get a clearer and boarder view of the perpetrators. To reduce the effect of probably insignificant alerts a threshold technique is used.
机译:互联网比以往任何时候都在改变计算。由于可能性和范围是无限的,因此恶意入侵的风险和机会也是如此。由于增加的连接性和广泛的财务可能性,越来越多的系统受到入侵者的攻击。入侵检测的常用方法之一是基于异常。基于网络的攻击可能发生在从应用程序到链接级别的各个级别。因此,潜在的攻击者或入侵者的数量非常多,因此几乎不可能“分析”实体并基于基于主机的配置文件中的异常来检测入侵。基于元信息,已对属于同一逻辑网络的警报进行了逻辑分组,以更清晰,更全面地了解肇事者。为了减少可能不重要的警报的影响,使用了阈值技术。

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