Analyzing the weighted dark networks using scale-free network approach

The task of identifying the main key nodes in the dark (covert) networks is very important for the researchers in the field of dark networks analysis. This analysis leads to locate the major nodes in the network as the functionality can be minimized by disrupting major key nodes in the network. In t...

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Main Authors:	Mahesar, Abdul Waheed, Waqas, Ahmad, Mahmood , Nadeem, Shah, Asadullah, Wahiddin, Mohamed Ridza
Format:	Article
Language:	English
Published:	World Scientific and Engineering Academy and Society 2015
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/43551/ http://irep.iium.edu.my/43551/ http://irep.iium.edu.my/43551/1/abdul-waheed-2015Analyzingweighteddarknetworks.pdf

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spelling	iium-435512017-08-08T03:17:04Z http://irep.iium.edu.my/43551/ Analyzing the weighted dark networks using scale-free network approach Mahesar, Abdul Waheed Waqas, Ahmad Mahmood , Nadeem Shah, Asadullah Wahiddin, Mohamed Ridza T Technology (General) The task of identifying the main key nodes in the dark (covert) networks is very important for the researchers in the field of dark networks analysis. This analysis leads to locate the major nodes in the network as the functionality can be minimized by disrupting major key nodes in the network. In this paper, we have primarily focused on two basic network analysis metrics, degree and betweenness centrality. Traditionally, both these centrality measures have been applied on the bases of number of links connected with the nodes but without considering link weights. Like many other networks, dark networks also follow scale-free behavior and thus follow the power-law distribution where few nodes have maximum links. This, inhomogeneous structure of network causes the creation of key nodes. In this research, we analyze the behavior of nodes in dark networks based on degree and betweenness centrality measures by using 9/11 terrorist network dataset. We analyzed both these measures with weighted and un-weighted links to prove that weighted networks are much closer to scale-free phenomenon as compared to un-weighted networks. World Scientific and Engineering Academy and Society 2015 Article PeerReviewed application/pdf en http://irep.iium.edu.my/43551/1/abdul-waheed-2015Analyzingweighteddarknetworks.pdf Mahesar, Abdul Waheed and Waqas, Ahmad and Mahmood , Nadeem and Shah, Asadullah and Wahiddin, Mohamed Ridza (2015) Analyzing the weighted dark networks using scale-free network approach. WSEAS Transactions on Computers, 14. pp. 748-759. ISSN 1109-2750 http://wseas.org/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Mahesar, Abdul Waheed Waqas, Ahmad Mahmood , Nadeem Shah, Asadullah Wahiddin, Mohamed Ridza Analyzing the weighted dark networks using scale-free network approach
description	The task of identifying the main key nodes in the dark (covert) networks is very important for the researchers in the field of dark networks analysis. This analysis leads to locate the major nodes in the network as the functionality can be minimized by disrupting major key nodes in the network. In this paper, we have primarily focused on two basic network analysis metrics, degree and betweenness centrality. Traditionally, both these centrality measures have been applied on the bases of number of links connected with the nodes but without considering link weights. Like many other networks, dark networks also follow scale-free behavior and thus follow the power-law distribution where few nodes have maximum links. This, inhomogeneous structure of network causes the creation of key nodes. In this research, we analyze the behavior of nodes in dark networks based on degree and betweenness centrality measures by using 9/11 terrorist network dataset. We analyzed both these measures with weighted and un-weighted links to prove that weighted networks are much closer to scale-free phenomenon as compared to un-weighted networks.
format	Article
author	Mahesar, Abdul Waheed Waqas, Ahmad Mahmood , Nadeem Shah, Asadullah Wahiddin, Mohamed Ridza
author_facet	Mahesar, Abdul Waheed Waqas, Ahmad Mahmood , Nadeem Shah, Asadullah Wahiddin, Mohamed Ridza
author_sort	Mahesar, Abdul Waheed
title	Analyzing the weighted dark networks using scale-free network approach
title_short	Analyzing the weighted dark networks using scale-free network approach
title_full	Analyzing the weighted dark networks using scale-free network approach
title_fullStr	Analyzing the weighted dark networks using scale-free network approach
title_full_unstemmed	Analyzing the weighted dark networks using scale-free network approach
title_sort	analyzing the weighted dark networks using scale-free network approach
publisher	World Scientific and Engineering Academy and Society
publishDate	2015
url	http://irep.iium.edu.my/43551/ http://irep.iium.edu.my/43551/ http://irep.iium.edu.my/43551/1/abdul-waheed-2015Analyzingweighteddarknetworks.pdf
first_indexed	2023-09-18T21:02:03Z
last_indexed	2023-09-18T21:02:03Z
_version_	1777410688872873984

Analyzing the weighted dark networks using scale-free network approach

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