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The Research and Design of Detection Method of DDoS Attack Based on Data Mining
Author: ShenZuo
Tutor: ZhangLaiShun
School: PLA Information Engineering University
Course: Applied Computer Technology
Keywords: Distributed denial of service attacks Association rule mining Global clustering Decision Tree
CLC: TP393.08
Type: Master's thesis
Year: 2006
Downloads: 151
Quote: 3
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Abstract
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DDoS ( Distributed Denial of Service ) attack is a major hazard for the Internet . It uses the Internet puppet host resource consumption between the destination host and legal clients , at the same time , it also has a negative effect , is often the source to the destination path causing network congestion . The attacker makes use of legitimate packets and change package information the description and filtration attack streams are difficult , the existing security mechanisms of these attacks can not provide effective protection measures need to pay a high price , in order to ensure safety . Association rules based on data mining methods , a DDoS attack detection system was designed and implemented from the point of view of traffic , it can effectively detect DDoS attacks . The main work is as follows : ( 1) analysis of the principles and typical DDoS attack attack tools , comparative study of a variety of detection model . (2) introduced several data mining techniques to explain the classical algorithm Apriori -based association rules and DHP discussed their limitations , and the improved algorithm DHPP . (3) using the global clustering algorithm to be pretreated to reduce the amount of data of the continuous information data packets . ( 4) using winpcap network packet capture, the double filtering methods deployed at the server and the router . (5 ) Visual C DDoS attack detection system based association rule mining , and simulation tests using NS-2 platform .
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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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