Title page for etd-0726112-150041


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URN etd-0726112-150041
Author Yu-Zhi Huang
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2011
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Detecting Attack Sequence in Cloud Based on Hidden Markov Model
Date of Defense 2012-07-16
Page Count 58
Keyword
  • Cloud Computing
  • Hidden Markov Model
  • Attack Plan
  • Abstract 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.
    Advisory Committee
  • Chia-Mei Chen - chair
  • Chun-I Fan - co-chair
  • D. J. Guan - advisor
  • Files
  • etd-0726112-150041.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2012-07-26

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