Detecting Attack Sequence in Cloud Based on Hidden Markov Model

碩士 === 國立中山大學 === 資訊工程學系研究所 === 100 === Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On th...

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Main Authors: Yu-Zhi Huang, 黃昱誌
Other Authors: D. J. Guan
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/07619966720241275689
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spelling ndltd-TW-100NSYS53920462015-10-13T21:22:19Z http://ndltd.ncl.edu.tw/handle/07619966720241275689 Detecting Attack Sequence in Cloud Based on Hidden Markov Model 基於隱藏式馬可夫模型之偵測雲端上攻擊序列 Yu-Zhi Huang 黃昱誌 碩士 國立中山大學 資訊工程學系研究所 100 Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On the other hand, hacker may facilitate cloud computing to launch larger range of attack, such as a request of port scan in cloud with virtual machines executing such malicious action. In addition, hacker may perform a sequence of attacks in order to compromise his target system in cloud, for example, evading an easy-to-exploit machine in a cloud and then using the previous compromised to attack the target. Such attack plan may be stealthy or inside the computing environment, so intrusion detection system or firewall has difficulty to identify it. The proposed detection system analyzes logs from cloud to extract the intensions of the actions recorded in logs. Stealthy reconnaissance actions are often neglected by administrator for the insignificant number of violations. Hidden Markov model is adopted to model the sequence of attack performed by hacker and such stealthy events in a long time frame will become significant in the state-aware model. The preliminary results show that the proposed system can identify such attack plans in the real network. D. J. Guan 官大智 2012 學位論文 ; thesis 58 zh-TW
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description 碩士 === 國立中山大學 === 資訊工程學系研究所 === 100 === Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On the other hand, hacker may facilitate cloud computing to launch larger range of attack, such as a request of port scan in cloud with virtual machines executing such malicious action. In addition, hacker may perform a sequence of attacks in order to compromise his target system in cloud, for example, evading an easy-to-exploit machine in a cloud and then using the previous compromised to attack the target. Such attack plan may be stealthy or inside the computing environment, so intrusion detection system or firewall has difficulty to identify it. The proposed detection system analyzes logs from cloud to extract the intensions of the actions recorded in logs. Stealthy reconnaissance actions are often neglected by administrator for the insignificant number of violations. Hidden Markov model is adopted to model the sequence of attack performed by hacker and such stealthy events in a long time frame will become significant in the state-aware model. The preliminary results show that the proposed system can identify such attack plans in the real network.
author2 D. J. Guan
author_facet D. J. Guan
Yu-Zhi Huang
黃昱誌
author Yu-Zhi Huang
黃昱誌
spellingShingle Yu-Zhi Huang
黃昱誌
Detecting Attack Sequence in Cloud Based on Hidden Markov Model
author_sort Yu-Zhi Huang
title Detecting Attack Sequence in Cloud Based on Hidden Markov Model
title_short Detecting Attack Sequence in Cloud Based on Hidden Markov Model
title_full Detecting Attack Sequence in Cloud Based on Hidden Markov Model
title_fullStr Detecting Attack Sequence in Cloud Based on Hidden Markov Model
title_full_unstemmed Detecting Attack Sequence in Cloud Based on Hidden Markov Model
title_sort detecting attack sequence in cloud based on hidden markov model
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/07619966720241275689
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