Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies

Kajian ini membentangkan penyelesaian, yang dikenali sebagai "Pemantauan Protokol Penemuan Tetangga Pintar (INDPMon)", berfungsi untuk meningkatkan tahap keselamatan rangkaian IPv6, dengan mengekalkan pengawasan yang berterusan berkenaan insiden Protokol Penemuan Tetangga (NDP), kelemah...

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Main Author:	Firas (M.H.) S., Najjar
Format:	Thesis
Language:	English
Published:	2016
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/32153/1/FIRAS_%28M.H.%29_S._NAJJAR_24%28NN%29.pdf
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id	my-usm-ep.32153
record_format	uketd_dc
spelling	my-usm-ep.321532019-04-12T05:25:15Z Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies 2016-08 Firas (M.H.) S., Najjar QA75.5-76.95 Electronic computers. Computer science Kajian ini membentangkan penyelesaian, yang dikenali sebagai "Pemantauan Protokol Penemuan Tetangga Pintar (INDPMon)", berfungsi untuk meningkatkan tahap keselamatan rangkaian IPv6, dengan mengekalkan pengawasan yang berterusan berkenaan insiden Protokol Penemuan Tetangga (NDP), kelemahan, dan kemungkinan serangan dalam membantu keputusan pengurusan risiko organisasi. INDPMon menggunakan pendekatan analisis rangkaian untuk memantau paket lapisan rangkaian, dan menggunakan kaedah protokol stateful untuk menggambarkan anomali protokol dengan tepat. Mesin keadaan terhingga terluas digunakan untuk memahami dan menganalisis tingkah laku dinamik protokol supaya sebarang peristiwa pelanggaran yang menyebabkan anomali NDP dapat dispesifikasi. Peristiwa yang paling diskriminatif dipilih untuk menentukan ciri-ciri set NDP yang akan digunakan untuk menggambarkan kelakuan NDP. Tapak ujian telah digunakan untuk menjana set data NDP dan proses awal prosedur dilakukan kepada set data NDP yang dijana bagi tujuan optimasi. Set data NDP bersama-sama ciri-ciri set NDP digunakan untuk membuat set data perwakilan ciri-ciri NDP yang merupakan tulang belakang INDPMon untuk ramalan dan klasifikasi keputusan. Buat masa ini, alat pemantauan NDP, yang dikenali sebagai NDPMon, adalah penyelesaian yang biasa dinamakan untuk memantau NDP. This research presents enhanced solution, called " Intelligent Neighbor Discovery Protocol Monitoring (INDPMon)", for improving the security of IPv6 networks by maintaining constant awareness of Neighbor Discovery Protocol (NDP) incidents, vulnerabilities, and attacks to support organizational risk management decisions. INDPMon adapts a network analysis approach to monitor network layer packets, and utilizes a stateful protocol methodology to precisely describe the protocol anomalies. Extended Finite State Machine is used to understand and analyze the dynamic behavior of the protocol in order to specify the violation events that cause NDP anomalies. The most discriminative events are selected to define the NDP features set which used to characterize the NDP behavior. Testbed has been used to generate NDP dataset and preprocessing procedures are applied to the generated NDP dataset for optimization. NDP dataset along with NDP features set are used to create a representative NDP features dataset which is the backbone of INDPMon for prediction and classifications decisions. Currently, NDP monitoring tool, called (NDPMon), is the commonly cited solution for monitoring NDP. 2016-08 Thesis http://eprints.usm.my/32153/ http://eprints.usm.my/32153/1/FIRAS_%28M.H.%29_S._NAJJAR_24%28NN%29.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat IPv6 Termaju Negara
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Firas (M.H.) S., Najjar Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
description	Kajian ini membentangkan penyelesaian, yang dikenali sebagai "Pemantauan Protokol Penemuan Tetangga Pintar (INDPMon)", berfungsi untuk meningkatkan tahap keselamatan rangkaian IPv6, dengan mengekalkan pengawasan yang berterusan berkenaan insiden Protokol Penemuan Tetangga (NDP), kelemahan, dan kemungkinan serangan dalam membantu keputusan pengurusan risiko organisasi. INDPMon menggunakan pendekatan analisis rangkaian untuk memantau paket lapisan rangkaian, dan menggunakan kaedah protokol stateful untuk menggambarkan anomali protokol dengan tepat. Mesin keadaan terhingga terluas digunakan untuk memahami dan menganalisis tingkah laku dinamik protokol supaya sebarang peristiwa pelanggaran yang menyebabkan anomali NDP dapat dispesifikasi. Peristiwa yang paling diskriminatif dipilih untuk menentukan ciri-ciri set NDP yang akan digunakan untuk menggambarkan kelakuan NDP. Tapak ujian telah digunakan untuk menjana set data NDP dan proses awal prosedur dilakukan kepada set data NDP yang dijana bagi tujuan optimasi. Set data NDP bersama-sama ciri-ciri set NDP digunakan untuk membuat set data perwakilan ciri-ciri NDP yang merupakan tulang belakang INDPMon untuk ramalan dan klasifikasi keputusan. Buat masa ini, alat pemantauan NDP, yang dikenali sebagai NDPMon, adalah penyelesaian yang biasa dinamakan untuk memantau NDP. This research presents enhanced solution, called " Intelligent Neighbor Discovery Protocol Monitoring (INDPMon)", for improving the security of IPv6 networks by maintaining constant awareness of Neighbor Discovery Protocol (NDP) incidents, vulnerabilities, and attacks to support organizational risk management decisions. INDPMon adapts a network analysis approach to monitor network layer packets, and utilizes a stateful protocol methodology to precisely describe the protocol anomalies. Extended Finite State Machine is used to understand and analyze the dynamic behavior of the protocol in order to specify the violation events that cause NDP anomalies. The most discriminative events are selected to define the NDP features set which used to characterize the NDP behavior. Testbed has been used to generate NDP dataset and preprocessing procedures are applied to the generated NDP dataset for optimization. NDP dataset along with NDP features set are used to create a representative NDP features dataset which is the backbone of INDPMon for prediction and classifications decisions. Currently, NDP monitoring tool, called (NDPMon), is the commonly cited solution for monitoring NDP.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Firas (M.H.) S., Najjar
author_facet	Firas (M.H.) S., Najjar
author_sort	Firas (M.H.) S., Najjar
title	Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
title_short	Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
title_full	Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
title_fullStr	Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
title_full_unstemmed	Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies
title_sort	enhanced techniques for detection and classification of neighbor discovery protocol anomalies
granting_institution	Universiti Sains Malaysia
granting_department	Pusat IPv6 Termaju Negara
publishDate	2016
url	http://eprints.usm.my/32153/1/FIRAS_%28M.H.%29_S._NAJJAR_24%28NN%29.pdf
_version_	1747820535601954816

Enhanced Techniques For Detection And Classification Of Neighbor Discovery Protocol Anomalies

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