Title page for etd-0904105-170131


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URN etd-0904105-170131
Author Kuang-Ming Wang
Author's Email Address No Public.
Statistics This thesis had been viewed 5571 times. Download 2372 times.
Department Computer Science and Engineering
Year 2004
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title A NetFlow Based Internet-worm Detecting System in Large Network
Date of Defense 2005-07-20
Page Count 49
Keyword
  • NetFlow
  • network security
  • network anomaly detection
  • Internet-worms
  • Abstract Internet-worms are a major threat to the security of today’s Internet and cause significant worldwide disruptions, a huge number of infected hosts generating overwhelming traffic will impact the performance of the Internet. Network managers have the duty to mitigate this issue . In this paper we propose an automated method for detecting Internet-worm in large network based on NetFlow. We also implement a prototype system – FloWorM which can help network managers to monitor suspect Internet-worms activities and identify their species in their managed networks. Our evaluation of the prototype system on real large and campus networks validates that it achieves pretty low false positive rate and good detecting rate.
    Advisory Committee
  • Pau-Choo Chung - chair
  • Chung-Nan Lee - co-chair
  • Mon-Yen Luo - co-chair
  • Yau-Hwang Kuo - co-chair
  • Chu-Sing Yang - advisor
  • Files
  • etd-0904105-170131.pdf
  • indicate in-campus access immediately and off_campus access in a year
    Date of Submission 2005-09-04

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