Enhanced AODV protocol against black hole attack based on classification algorithm
Other Title(s)
بروتوكول AODV محسن للكشف عن هجمات الثقب الأسود باستخدام خوارزمية تصنيف
Dissertant
Athaminah, al-Muhannad Muhsin Ali
Thesis advisor
University
Philadelphia University
Faculty
Faculty of Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2018
English Abstract
Covering areas that do not have ready infrastructures to support network connections, has become one of the most demand topics.
Mobile ad hoc network (MANET).
Were the solution for this problem, were protocols like Ad Hoc On-Demand Distance Vector (AODV) take action to manage the devices inside.
As a result of such network characteristics AODV protocol were vulnerable to list of attacks like denial-of-service (DOS).
Attacks which contain attacks like black hole and worm whole attacks.
In this research new algorithm for black hole attack detection and prevention were presented based on four features extracted from the AODV protocol which are (Total number of Packets Dropped, Route Error, Rout Reply, and sequence number) .Ready data set was used to select best features related to black hole attack using symmetrical uncertainty (SU) feature selector based on WEKA tool.
The four features were evaluated by classification method called J48 in order to proof their capability of defining black hole nodes.
Moreover, the presented algorithm implements very simple test classification criteria over the regular AODV protocol to allow detection and sharing the black nodes identities.
The results of the experimental results were implemented using Global Mobile Information System Simulator(GlomoSim) simulator over 50 nodes, and compared to 3 other previously proposed algorithms (Standard AODV, behavior-driven development (BDD-AODV), and Artificial neural network Ad Hoc On-Demand Distance Vector(ANN-AODV), where the new proposed algorithm proofed its capability in detecting and preventing black hole attacks with higher efficiency average on END-TO-END time delay, lower overhead factor, and higher packet delivery ration packet delivery ratio (PDR) than all other three algorithms.
Main Subjects
Information Technology and Computer Science
Topics
No. of Pages
64
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Literature review.
Chapter Three : Proposed Methodology (Enhanced AODV).
Chapter Four : Results and discussion.
Chapter Five : Conclusions and future works.
References.
American Psychological Association (APA)
Athaminah, al-Muhannad Muhsin Ali. (2018). Enhanced AODV protocol against black hole attack based on classification algorithm. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-955251
Modern Language Association (MLA)
Athaminah, al-Muhannad Muhsin Ali. Enhanced AODV protocol against black hole attack based on classification algorithm. (Master's theses Theses and Dissertations Master). Philadelphia University. (2018).
https://search.emarefa.net/detail/BIM-955251
American Medical Association (AMA)
Athaminah, al-Muhannad Muhsin Ali. (2018). Enhanced AODV protocol against black hole attack based on classification algorithm. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-955251
Language
English
Data Type
Arab Theses
Record ID
BIM-955251
