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http://hdl.handle.net/10603/308347
Title: | Effective modelling and analysis of complex network for predicting covert organizational structures |
Researcher: | Kiruthiga A |
Guide(s): | bBose S |
Keywords: | Engineering and Technology Computer Science Computer Science Information Systems predicting covert complex network |
University: | Anna University |
Completed Date: | 2019 |
Abstract: | Covert Networks are social networks with many secret elements in it. The networks formed by terrorists to achieve their target. Terrorism is a major threat to humanity over centuries and the governments of countries around the world strive hard to prevent terrorist attacks in every possible way. It is very much primary to understand how covert networks work before attempting to prevent their attack, since incorrect attempts to destroy the enemy, makes the enemy even more stronger than before. To understand how covert networks form and to understand elements of its structure, complex network phenomenon and Social Network Analysis (SNA) are used as tools. A network with non-trivial topological features and with patterns of connectivity between random and regular pattern is called as complex network. Complex Network Theory allows to mathematically model the complex organizational structures and real world networks are analysed to understand the properties underlying them. By modelling real-world networks as complex networks, graph theoretic metrics can be applied on real-world networks to analyze their characteristics. From real-world theoretical models, simulated networks can be generated and it can be compared with real-world networks for validation. In this research work, covert networks are modeled, simulated and analyzed using complex network theory to get a better insight into the covert networks and the simulated networks are compared with the real-world covert network instances. The proposed Covert Organizational Structure Investigator (COSI) system Identifies, Models and Analyzes the covert organizational structures using Complex Network Theory and Graph modelling newline |
Pagination: | xxiii, 193p. |
URI: | http://hdl.handle.net/10603/308347 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 80.1 kB | Adobe PDF | View/Open |
02_certificates.pdf | 411.34 kB | Adobe PDF | View/Open | |
03_abstracts.pdf | 65.48 kB | Adobe PDF | View/Open | |
04_acknowledgements.pdf | 63.57 kB | Adobe PDF | View/Open | |
05_contents.pdf | 80.31 kB | Adobe PDF | View/Open | |
06_listofabbreviations.pdf | 132.56 kB | Adobe PDF | View/Open | |
07_chapter1.pdf | 99.52 kB | Adobe PDF | View/Open | |
08_chapter2.pdf | 99.58 kB | Adobe PDF | View/Open | |
09_chapter3.pdf | 102.96 kB | Adobe PDF | View/Open | |
10_chapter4.pdf | 257.53 kB | Adobe PDF | View/Open | |
11_chapter5.pdf | 372.79 kB | Adobe PDF | View/Open | |
12_chapter6.pdf | 674.52 kB | Adobe PDF | View/Open | |
13_chapter7.pdf | 491.74 kB | Adobe PDF | View/Open | |
14_chapter8.pdf | 380.67 kB | Adobe PDF | View/Open | |
15_conclusion.pdf | 74.29 kB | Adobe PDF | View/Open | |
16_references.pdf | 86.31 kB | Adobe PDF | View/Open | |
17_listofpublications.pdf | 65.9 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 82.17 kB | Adobe PDF | View/Open |
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