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Intrusion Detection Algorithm Based on Danger Theory

Author: YangQiang
Tutor: XuJia
School: University of Electronic Science and Technology
Course: Computational Mathematics
Keywords: Danger Theory Intrusion Detection System Artificial Immune System
CLC: TP393.08
Type: Master's thesis
Year: 2009
Downloads: 83
Quote: 1
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Abstract


Intrusion detection is an important topic in the field of information security . Intrusion detection system (Intrusion Detection System, IDS) as a proactive information security technology , you can maximize the security capabilities of the system to reduce the external threat . Build intelligent IDS system ( Intelligent IDS, IIDS ) is to improve the the IDS system performance key . Artificial immune system simulation of biological immune system tolerance, robustness , self- adaptability , diversity , etc. , have better intelligence , intrusion detection system low accuracy , false negative rate and false alarm rate can be a good solution high shortcomings, while unknown intrusion better detection capabilities . Immune danger theory is popular over the past decade in the new theory of the immune academia . It is that the immune system is not to distinguish between self and non-self- body , but to distinguish between the presence or absence of danger signals . Although the theory has not been widely accepted as a simulation of a biological immune system , it can be extended to be applied to the field of artificial immune . The main work of this paper is as follows : first introduced the background , definitions and functions of intrusion detection , the introduction of some commonly used intrusion detection method , introduced the artificial immune theory and algorithms . Dangerous theory is too complex and difficult to understand , this paper according to the application areas do dangerous theory the simplified modified to make it suitable for intrusion detection . Suse Linux10 system using the C programming language algorithm design simulation of IDS model based on immune danger test using KDDCup99 datasets . Finally , the application of the algorithm to the actual network environment gives practical suggestions .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Computer network > General issues > Computer Network Security
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