Research on Differentiation Model and Application of Dendritic Cells in Artificial Immune System

NI Jian-cheng; LI Zhi-shu; SUN Ji-rong; ZHOU Li-ping

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Research on Differentiation Model and Application of Dendritic Cells in Artificial Immune System

更新时间：2025-07-16

- Research on Differentiation Model and Application of Dendritic Cells in Artificial Immune System
- Acta Electronica Sinica Vol. 36, Issue 11, Pages: 2210-2215(2008)
- 作者机构：
  
  1. 曲阜师范大学计算机学院,山东,日照,276826
  2. 四川大学计算机学院,四川,成都,610065
  3. 曲阜师范大学计算机学院山东日照,276826
  4. 四川大学计算机学院四川成都,610065
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393
- Published：2008
- 稿件说明：
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NI Jian-cheng, LI Zhi-shu, SUN Ji-rong, et al. Research on Differentiation Model and Application of Dendritic Cells in Artificial Immune System[J]. Acta Electronica Sinica, 2008, 36(11): 2210-2215.
DOI：

NI Jian-cheng, LI Zhi-shu, SUN Ji-rong, et al. Research on Differentiation Model and Application of Dendritic Cells in Artificial Immune System[J]. Acta Electronica Sinica, 2008, 36(11): 2210-2215. DOI：

摘要

树突状细胞(Dendritic Cell

DC)是先天性免疫系统的重要组件

其分化机制是正确引发与调节适应性免疫响应的关键.首先

在描述DC分化的生物机理基础上

抽象出了DC的信息处理过程.其次

在阐释DAMP等四类外部信号的含义与功能、信号融合过程的基础上

定义了未成熟、完全成熟与半成熟DC Agent

刻画了它们的分化数学模型与演化过程.最后

论证了各类DC Agent数量与生存周期之间的关系.实验结果表明DC分化机制对降低入侵检测误报率、实现自我调节和进一步增强计算机系统安全具有重要的理论意义与应用价值.

Abstract

The most one critical component in innate immune system is dentritic cell (DC)

which differentiation mechanism is also the key to initiate and control adaptive immune response correctly.Firstly

based on describing biological principles of DCs differentiation

the information processing procedure for DCs is abstracted.Secondly

laying the foundation of illustrating four-category behavioral signals such as danger-associate molecular patterns et al.

and informational fusion procedure

agents including immature

fully mature and semi-mature DCs are defined

and detailed mathematical differentiation model are formulized and deducted.Lastly

several relations between quantity and lifecycle of different Agent category are proved.Simulation testing results demonstrate that DCs differentiation mechanism has theoretical significance and practical value on computer security besides decreasing false positive rate as well as achieving homeostasis for intrusion detection systems.

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