通过分割将实时的分析与树突状细胞算法集成
Integrating Real-Time Analysis With The Dendritic Cell Algorithm Through Segmentation
摘要：
作为一种免疫算法，树突细胞算法（DCA）已被应用于一系列问题，特别是在入侵检测领域。理想情况下，入侵检测应该实时的【形】执行，以便在误用发生时立即持续检测。因此，由入侵检测系统执行的分析过程必须实时的【形】或接近实时的【形】。DCA的分析过程目前是离线执行的，因此，为了提高算法的性能，我们建议开发一个实时的【形】分析组件。开发的第一步是将分割应用于DCA。这涉及将DCA的当前输出分割成切片并以各种方式执行分析。本文介绍并测试了两种分割方法，即基于抗原的分割（ABS）和基于时间的分割（TBS）。相应的实验结果表明，在某些情况下，与没有分割的标准DCA相比，应用分割会产生不同的和明显更好的结果。因此，我们得出结论，分割是适用于DCA的实时的【形】分析的目的。
英文摘要：
As an immune inspired algorithm, the Dendritic Cell Algorithm (DCA) has been applied to a range of problems, particularly in the area of intrusion detection. Ideally, the intrusion detection should be performed in real-time, to continuously detect misuses as soon as they occur. Consequently, the analysis process performed by an intrusion detection system must operate in real-time or near-to real-time. The analysis process of the DCA is currently performed offline, therefore to improve the algorithm's performance we suggest the development of a real-time analysis component. The initial step of the development is to apply segmentation to the DCA. This involves segmenting the current output of the DCA into slices and performing the analysis in various ways. Two segmentation approaches are introduced and tested in this paper, namely antigen based segmentation (ABS) and time based segmentation (TBS). The results of the corresponding experiments suggest that applying segmentation produces different and significantly better results in some cases, when compared to the standard DCA without segmentation. Therefore, we conclude that the segmentation is applicable to the DCA for the purpose of real-time analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
