Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism

碩士 === 國立臺灣科技大學 === 資訊工程系 === 107 === The existing security equipment detects attack by applying host-based intrusion detection system(HIDS), User and Entity Behavior Analytics(UEBA) and anti-virus software. Unfortunately, huge amounts of logs are generated by the equipment, and correlating all of t...

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Main Authors: Chi-Yuan Hsieh, 謝奇元
Other Authors: Hahn-Ming Lee
Format: Others
Language:en_US
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/4f28m3
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spelling ndltd-TW-107NTUS53920012019-05-16T00:59:41Z http://ndltd.ncl.edu.tw/handle/4f28m3 Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism 透過遞迴支配機制從複雜系統呼叫圖搜尋入侵者關鍵軌跡 Chi-Yuan Hsieh 謝奇元 碩士 國立臺灣科技大學 資訊工程系 107 The existing security equipment detects attack by applying host-based intrusion detection system(HIDS), User and Entity Behavior Analytics(UEBA) and anti-virus software. Unfortunately, huge amounts of logs are generated by the equipment, and correlating all of the logs is a very time-consuming task. In the end, only fragments of information are obtained, such as unusual system login behaviors, suspicious Command-and-control(C&C) servers and malware, which are unable to describe the attack scenarios. As a result, forensics experts need to manually investigate the key intrusion of the attacks. In this study, our purpose is to reduce the costs of manual attack intrusion investigation. We propose a method that explores the intruder key trace by examining dominators of system-level logs and design a recursive dominator mechanism to identify whether the events are related to the attacks. The main contributions of the study are as follows: (1) Filtering 98.94% of normal behaviors; (2) Recovering the key trace of the attack with a 92.85% recall rate; (3) Constructing the attack chain with information fragments. Hahn-Ming Lee 李漢銘 2018 學位論文 ; thesis 54 en_US
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description 碩士 === 國立臺灣科技大學 === 資訊工程系 === 107 === The existing security equipment detects attack by applying host-based intrusion detection system(HIDS), User and Entity Behavior Analytics(UEBA) and anti-virus software. Unfortunately, huge amounts of logs are generated by the equipment, and correlating all of the logs is a very time-consuming task. In the end, only fragments of information are obtained, such as unusual system login behaviors, suspicious Command-and-control(C&C) servers and malware, which are unable to describe the attack scenarios. As a result, forensics experts need to manually investigate the key intrusion of the attacks. In this study, our purpose is to reduce the costs of manual attack intrusion investigation. We propose a method that explores the intruder key trace by examining dominators of system-level logs and design a recursive dominator mechanism to identify whether the events are related to the attacks. The main contributions of the study are as follows: (1) Filtering 98.94% of normal behaviors; (2) Recovering the key trace of the attack with a 92.85% recall rate; (3) Constructing the attack chain with information fragments.
author2 Hahn-Ming Lee
author_facet Hahn-Ming Lee
Chi-Yuan Hsieh
謝奇元
author Chi-Yuan Hsieh
謝奇元
spellingShingle Chi-Yuan Hsieh
謝奇元
Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
author_sort Chi-Yuan Hsieh
title Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
title_short Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
title_full Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
title_fullStr Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
title_full_unstemmed Exploring Intruder Key Trace based on Complicated System Call Graph by Recursive Dominator Mechanism
title_sort exploring intruder key trace based on complicated system call graph by recursive dominator mechanism
publishDate 2018
url http://ndltd.ncl.edu.tw/handle/4f28m3
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