Detecting the Web Server from DDoS Attacks by Using Three-Tier Model

碩士 === 國立臺灣科技大學 === 資訊工程系 === 94 === According to FBI 2003 Computer Crime and Security Survey Result, Distributed Denial of Service Attack is the second dangerous network attack in the world. The attacker use abnormal activities to consume the system resource or to degrade the performance of network...

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Main Authors: Guan-Ci Huang, 黃冠錡
Other Authors: Shi-Jinn Horug
Format: Others
Language:en_US
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/72199146933221755182
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spelling ndltd-TW-094NTUST3920092015-10-13T11:57:24Z http://ndltd.ncl.edu.tw/handle/72199146933221755182 Detecting the Web Server from DDoS Attacks by Using Three-Tier Model 用三階層是模組於偵測伺服器上的DDoS攻擊之研究 Guan-Ci Huang 黃冠錡 碩士 國立臺灣科技大學 資訊工程系 94 According to FBI 2003 Computer Crime and Security Survey Result, Distributed Denial of Service Attack is the second dangerous network attack in the world. The attacker use abnormal activities to consume the system resource or to degrade the performance of network instead of intruding the system itself. Detection mechanisms are researched that are able to detect the abnormal activities when the attackers use the large amount of packets to break the system down in the development of DDoS. However, the changeable frequency mode will be the tendency in the future. In this paper, we proposed the three layers detection mechanism which can look for the changeable frequency attack mode. Firstly, we will analyze which fields in the packet may be our features. After analyzing, the similar features will be grouped into each layer which quantifies the normal service behavior precisely according to their characteristics. It is easy and immediate to detect the abnormal behavior when the attacks occur. We implement our proposed mechanism in the NTUST’s Web Server. We will attack the Web server in practice to observe the difference for beginning to end. And our proposed mechanism can reach a higher performance. Shi-Jinn Horug 洪西進 2006 學位論文 ; thesis 76 en_US
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description 碩士 === 國立臺灣科技大學 === 資訊工程系 === 94 === According to FBI 2003 Computer Crime and Security Survey Result, Distributed Denial of Service Attack is the second dangerous network attack in the world. The attacker use abnormal activities to consume the system resource or to degrade the performance of network instead of intruding the system itself. Detection mechanisms are researched that are able to detect the abnormal activities when the attackers use the large amount of packets to break the system down in the development of DDoS. However, the changeable frequency mode will be the tendency in the future. In this paper, we proposed the three layers detection mechanism which can look for the changeable frequency attack mode. Firstly, we will analyze which fields in the packet may be our features. After analyzing, the similar features will be grouped into each layer which quantifies the normal service behavior precisely according to their characteristics. It is easy and immediate to detect the abnormal behavior when the attacks occur. We implement our proposed mechanism in the NTUST’s Web Server. We will attack the Web server in practice to observe the difference for beginning to end. And our proposed mechanism can reach a higher performance.
author2 Shi-Jinn Horug
author_facet Shi-Jinn Horug
Guan-Ci Huang
黃冠錡
author Guan-Ci Huang
黃冠錡
spellingShingle Guan-Ci Huang
黃冠錡
Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
author_sort Guan-Ci Huang
title Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
title_short Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
title_full Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
title_fullStr Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
title_full_unstemmed Detecting the Web Server from DDoS Attacks by Using Three-Tier Model
title_sort detecting the web server from ddos attacks by using three-tier model
publishDate 2006
url http://ndltd.ncl.edu.tw/handle/72199146933221755182
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