基于树突状细胞算法的恶意TCP端口扫描检测方法

Nuha Almasalmeh, Firas Saidi, Z. Trabelsi
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引用次数: 2

摘要

网络攻击的扩散带来了开发复杂检测工具的迫切需要。其中一些工具基于受人类免疫系统(HIS)启发的算法。树突状细胞算法(Dendritic Cell Algorithm, DCA)就是一种基于Danger模型的基于HIS的算法。为了检测DoS攻击,本研究分析了两种DCA算法(确定性DCA和经典DCA)。此外,本文还讨论了对DCA算法的改进,以涵盖恶意TCP端口扫描的检测。通过使用不同的用例,累积评价和结果,证明了DCA算法在端口扫描检测中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Dendritic Cell Algorithm Based Approach for Malicious TCP Port Scanning Detection
The proliferation of cyber-attacks brings up an urgent need to develop sophisticated detection tools. Some of these tools are based on algorithms inspired from the Human Immune System (HIS). The Dendritic Cell Algorithm (DCA) is one of such HIS inspired methods, which is based on the Danger model. In the current study, two kinds of DCA algorithms (deterministic and classical DCA) are analyzed in order to detect DoS attacks. Moreover, this paper discusses the enhancement of the DCA algorithm to cover the detection of malicious TCP port scanning. By using different use-cases, the evaluation and results are accumulated to show the efficiency of the DCA algorithm used in the Port scanning detection.
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