摘要翻译：
树突状细胞算法(DCA)作为一种受免疫启发的算法，已被应用于一系列问题，尤其是在入侵检测领域。理想情况下，入侵检测应该实时执行，以便在误用发生时立即持续检测它们。因此，入侵检测系统执行的分析过程必须是实时或接近实时的。目前DCA的分析过程是离线进行的，因此为了提高算法的性能，我们建议开发一个实时分析组件。开发的第一步是将分段应用于DCA。这涉及到将DCA的当前输出分段为切片，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，与不进行分割的标准DCA相比，应用分割可以产生不同的结果，但效果明显更好。因此，我们的结论是，分割适用于DCA的目的，以实时分析。
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英文标题：
《Integrating Real-Time Analysis With The Dendritic Cell Algorithm Through
  Segmentation》
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作者：
Feng Gu, Julie Greensmith, Uwe Aickelin
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最新提交年份：
2010
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Neural and Evolutionary Computing        神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Cryptography and Security        密码学与安全
分类描述：Covers all areas of cryptography and security including authentication, public key cryptosytems, proof-carrying code, etc. Roughly includes material in ACM Subject Classes D.4.6 and E.3.
涵盖密码学和安全的所有领域，包括认证、公钥密码系统、携带证明的代码等。大致包括ACM主题课程D.4.6和E.3中的材料。
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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.
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PDF链接：
https://arxiv.org/pdf/1003.4140