Storage based intrusion detection system

This project is a collaboration project between Nanyang Technological University (NTU) and A*STAR Research Institute, Data Storage Institute (DSI) Network Storage Technology Division. In this research, an infrastructure of network test bed is built as the first phase of the project. In the second...

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Bibliographic Details
Main Author: Lwin, Maung Chan Myae.
Other Authors: Ma Maode
Format: Final Year Project (FYP)
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/17965
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author Lwin, Maung Chan Myae.
author2 Ma Maode
author_facet Ma Maode
Lwin, Maung Chan Myae.
author_sort Lwin, Maung Chan Myae.
collection NTU
description This project is a collaboration project between Nanyang Technological University (NTU) and A*STAR Research Institute, Data Storage Institute (DSI) Network Storage Technology Division. In this research, an infrastructure of network test bed is built as the first phase of the project. In the second phase, network attack models are trained by classifying аttаcks based on the security mechanism targeted by the аttаcker. The achievement of the study is some known attack models have been trained and the behavior on these types of attacks can be prevented if the illegitimate user is intruding with such kind of behaviors. The system incorporates the latest state of the art technologies of intrusion detection and prevention technologies, and leverages on the network storage capabilities of NST, DSI to develop a proof of concept product for the needs of the network storage industry. Based on the trained models, the intrusion of such known attacks can be prevented and detected in future in the network test bed which plays the major role for storage based intrusion detection system.
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spelling ntu-10356/179652023-07-07T15:47:27Z Storage based intrusion detection system Lwin, Maung Chan Myae. Ma Maode School of Electrical and Electronic Engineering A*STAR Data Storage Institute Network Storage Technology Division DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This project is a collaboration project between Nanyang Technological University (NTU) and A*STAR Research Institute, Data Storage Institute (DSI) Network Storage Technology Division. In this research, an infrastructure of network test bed is built as the first phase of the project. In the second phase, network attack models are trained by classifying аttаcks based on the security mechanism targeted by the аttаcker. The achievement of the study is some known attack models have been trained and the behavior on these types of attacks can be prevented if the illegitimate user is intruding with such kind of behaviors. The system incorporates the latest state of the art technologies of intrusion detection and prevention technologies, and leverages on the network storage capabilities of NST, DSI to develop a proof of concept product for the needs of the network storage industry. Based on the trained models, the intrusion of such known attacks can be prevented and detected in future in the network test bed which plays the major role for storage based intrusion detection system. Bachelor of Engineering 2009-06-18T04:18:37Z 2009-06-18T04:18:37Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17965 en Nanyang Technological University 85 p. application/pdf
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Lwin, Maung Chan Myae.
Storage based intrusion detection system
title Storage based intrusion detection system
title_full Storage based intrusion detection system
title_fullStr Storage based intrusion detection system
title_full_unstemmed Storage based intrusion detection system
title_short Storage based intrusion detection system
title_sort storage based intrusion detection system
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
url http://hdl.handle.net/10356/17965
work_keys_str_mv AT lwinmaungchanmyae storagebasedintrusiondetectionsystem