计算机免疫危险理论中危险信号的提取方法研究

计算机科学 ›› 2015, Vol. 42 ›› Issue (8): 170-174.

计算机免疫危险理论中危险信号的提取方法研究

杨超,李涛

湖北大学计算机与信息工程学院武汉430062,武汉科技大学计算机科学与技术学院武汉430065

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受国家自然科学基金项目(61170306),湖北省自然科学基金面上项目(2014CFB536) ,湖北省教育厅人文社科重点项目(2012D111)资助

Research of Danger Signal Extraction Based on Changes in Danger Theory

YANG Chao and LI Tao

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 危险理论是人工免疫系统的一个重要研究分支,它从危险的角度出发对免疫系统的工作原理进行了新的阐述,目前已广泛应用于入侵检测、机器学习和数据挖掘等领域。建立危险理论模型的首要问题是如何自适应地提取危险信号。从变化导致危险这一思想出发,建立了一套基于变化特征的危险信号自适应提取模型；针对不同类型系统资源的特点,设计了基于值变化和特征变化的两种危险信号提取方法。同时,通过实验验证了该模型在不依赖先验知识的情况下,能够自适应地提取危险信号。

关键词: 人工免疫系统,危险理论,危险信号,变化提取

Abstract: Danger theory is an important research branch in artificial immune system.It starts from the perspective of danger to describe the working principle of immune system in a new way,which has been widely used in intrusion detection,machine learning,data mining and so on.The primary issue of establishing a danger theory model is how to extract danger signals adaptively.This paper started from the main idea of changes leading to danger,and established an adaptive danger signal extraction model based on finding changes.According to the characteristics of different types of system resources,it designed two danger signal extraction methods:value changes and feature changes.The experiment verifies that this model can adaptively extract danger signals without relying on prior knowledge.

Key words: Artificial immune system,Danger theory,Danger signal,Change extraction

杨超,李涛. 计算机免疫危险理论中危险信号的提取方法研究[J]. 计算机科学, 2015, 42(8): 170-174. https://doi.org/

YANG Chao and LI Tao. Research of Danger Signal Extraction Based on Changes in Danger Theory[J]. Computer Science, 2015, 42(8): 170-174. https://doi.org/

参考文献

[1] Aickelin U,Cayzer S.The Danger Theory and Its Application to Artificial Immune Systems [C]∥Proceedings of the 1st International Conference on Artificial Immune Systems(ICARIS-2002).Canterbury,UK,2002:141-148
[2] Vella M,Roper M,Terzis S.Danger Theory and Intrusion Detection:Possibilities and Limitations of the Analogy[C]∥Proceedings of the International Conference on Artificial Immune Systems(ICARIS-2010).2010:276-289
[3] Greensmith J,Aickelin U.Dendritic Cells for SYN Scan Detection[C]∥Proceedings of 9th Annual Conference on Genetic and Evolutionary Computation.2007:49-56
[4] Zhu Y,Tan Y.A Danger Theory Inspired Learning Model and Its Application to Spam Detection[C]∥Advances in Swarm Intelligence:Proceedings of 2nd International Conference on ICSI 2011.Springer,2011:382-389
[5] Musselle C.Rethinking Concepts of the Dendritic Cell Algo-rithm for Multiple Data Stream Analysis[C]∥Proceedings of the 11st International Conference on Artificial Immune Systems(ICARIS-2012).Berlin Heidelberg,2012:246-259
[6] Gu F,Greensmith J,Aickelin U.The Dendritic Cell Algorithm for Intrusion Detection [M]∥Biologically Inspired Networking and Sensing:Algorithms and Architectures.2012
[7] Vella M,Roper M,Terzis S.Danger Theory and Intrusion Detection:Possibilities and Limitations[C]∥Proceedings of 9th International Conference on Artificial Immune Systems(ICARIS 2010).2010:276-289
[8] Bianchi M E.DAMPs,PAMPs and alarmins:all we need toknow about danger [J].Journal of Leukocyte Biology,2007,81(1):1-5
[9] Greensmith J,Aickelin U.Dendritic Cells for SYN Scan Detection [C]∥Proceedings of 9th Annual Conference on Genetic and Evolutionary Computation.2007:49-56
[10] Greensmith J,Aickelin U,Twycross.Articulation and Clarification of the Dendritic Cell Algorithm [C]∥Artifical Immune Systems:Proceedings of the 5th International Conference on Artificial Immune Systems(ICARIS).Springer,2006:404-417
[11] Oates R,Greensmith J,Aickelin U,et al.The Application of a Dendritic Cell Algorithm to a Robotic Classifier [C]∥Artificial Immune Systems:Proceedings of 6th International Conference on ICARIS 2007.Springer,2007:204-215
[12] Al-Hammadi Y,Aickelin U,Greensmith J.DCA for bot detection [C]∥Evolutionary Computation(CEC 2008).2008:1807-1816
[13] Vella M,Roper M.Characterization of a danger context for detecting novel attacks targeting Web-based systems [EB/OL].http://www.cis.strath.ac.uk/~mv/trep2.pdf.2010
[14] 陈慰峰.医学免疫学[M].北京:人民卫生出版社,2000 Chen Wei-feng.Medical Immunology [M].Beijing:People’s Medical Publishing House Press,2000
[15] Li Y,Chen J,Gong P,et al.Study on Land Cover Change Detection Method Based on NDVI Time Series Datasets Change Detection Indexes Design [J].Journal of Basic Science and Engineering, 2005,13(3):261-275
[16] Yang Chao,Liang Yi-wen,Liu Ao-lin.The Danger Sensed Methodby Feature Changes [J].Energy Procedia 13,2011:4429-4437

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