Morwilog:一个基于aco的系统,用于概述多步骤攻击

Julio Navarro-Lara, A. Deruyver, P. Parrend
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引用次数: 12

摘要

威胁检测是保护网络的基本机制之一,预防是不够的。发现攻击是困难的,因为最有害的攻击是专门针对特定受害者准备的,并且是第一次制作的。无论现在使用的自动检测方法多么有效,对它们的检测仍然需要人类专家的贡献。此外,在许多情况下,入侵只能通过分析其对网络中多个元素的影响来有效检测。事件和警报回忆提供了一种方法来集中来自异构源集的信息。然后,可以将其规范化为通用语言,并由安全系统进行整体分析。在本文中,我们提出了Morwilog,这是一种anti -inspired方法,用于区分属于同一复杂攻击的操作之间的关系。Morwilog被认为是一个警报关联的框架,将被集成到一个多模块安全系统中。由于人类安全专家的反馈,强化学习被纳入其中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Morwilog: an ACO-based system for outlining multi-step attacks
Threat detection is one of the basic mechanisms for protecting a network, as prevention does not suffice. Finding an attack is difficult because the most harmful ones are specially prepared against a specific victim and crafted for the first time. The contribution of a human expert is still needed for their detection, no matter how effective automatic methods used nowadays can appear. Moreover, in many occasions intrusions can only be efficiently detected by analyzing its effects on more than one element in the network. Event and alert recollection offers a way to centralize information from a heterogeneous set of sources. Then, it can be normalized to a common language and analyzed as a whole by a security system. In this paper we propose Morwilog, an ant-inspired method for standing out the relationship between actions belonging to the same complex attack. Morwilog is conceived as a framework for alert correlation to be integrated in a multi-modular security system. Reinforcement learning is incorporated to it thanks to feedback from a human security expert.
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