Novel intrusion prevention and detection methods

V. Jotsov
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Abstract

Analysis of contemporary information security systems (ISS) and especially the case of intrusion detection systems (IDS) shows us few character negative features and drawbacks. Original methods and combined anomaly and signature IDS applications are presented in the paper. Human-centered methods INCONSISTENCY, FUNNEL, CALEIDOSCOPE and CROSSWORD interact on a competitive principle and are controlled by a synthetic metamethod SMM. A research is going on for the possibilities of including other machine learning and data mining methods under the general control of SMM. Their applications aim at computational discovery and knowledge acquisition. It is reinforced by identification and resolution of contradictions, self-learning and other methods for analysis of different types of models from the ISS domain. The complexity of application results is considered. The data analysis in the field frequently needs an act of creation especially if it is applied in a knowledge-poor environment. It is shown that even in this case the creative processes are based on applications of clear and well-formalized methods.
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新的入侵防御和检测方法
通过对当代信息安全系统,特别是入侵检测系统的分析,我们发现了一些信息安全系统的缺点和缺点。本文介绍了原始的检测方法,并结合了异常检测和签名检测的应用。不一致性、漏斗、万花筒和纵横字谜以竞争原则相互作用,并由综合元方法SMM控制。将其他机器学习和数据挖掘方法纳入SMM的一般控制下的可能性正在进行研究。它们的应用旨在计算发现和知识获取。通过识别和解决矛盾,自我学习和其他方法来分析来自ISS领域的不同类型的模型,从而加强了它。考虑了应用结果的复杂性。现场的数据分析往往需要创造性的行为,特别是在知识贫乏的环境中应用时。它表明,即使在这种情况下,创造性的过程是基于应用的清晰和良好的形式化的方法。
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