Analyzing the dynamics behaviour of fast-flux domain name system through visualization /

As attempts to thwart cyber crime have intensified, so have innovations in how cybercriminals' provision their infrastructure to dodge detection and take-down. Today, a growing, sophisticated technique called Fast-Flux Service Networks (FFSN) poses a major problem to Internet security. They are...

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Bibliographic Details
Main Author: Andi Fitriah Binti Abdul Kadir
Format: Thesis
Language:English
Published: Kuala Lumpur : Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2013
Subjects:
Online Access:http://studentrepo.iium.edu.my/handle/123456789/5624
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040 |a UIAM  |b eng 
041 |a eng 
043 |a a-my--- 
050 0 0 |a TK5105.59 
100 0 |a Andi Fitriah Binti Abdul Kadir 
245 1 |a Analyzing the dynamics behaviour of fast-flux domain name system through visualization /  |c by Andi Fitriah Binti Abdul Kadir 
260 |a Kuala Lumpur :  |b Kulliyyah of Information and Communication Technology, International Islamic University Malaysia,  |c 2013 
300 |a xxii, 176 leaves :  |b ill. ;  |c 30cm. 
500 |a Abstracts in English and Arabic. 
500 |a "A thesis submitted in fulfilment of the requirement for the degree of Master of Computer Science."--On t.p. 
502 |a Thesis (MCS)--International Islamic University Malaysia, 2013. 
504 |a Includes bibliographical references (leaves 162-167). 
520 |a As attempts to thwart cyber crime have intensified, so have innovations in how cybercriminals' provision their infrastructure to dodge detection and take-down. Today, a growing, sophisticated technique called Fast-Flux Service Networks (FFSN) poses a major problem to Internet security. They are increasingly used in many illegal practices including money mule recruitment sites, distribution of malware downloads, illegal adult content and other forms of Internet fraud. Essentially, FFSN were first used as a Domain Name Server (DNS) switching mechanism that combine distributed command and control, web-based load-balancing, and proxy redirection. However, cybercriminals are making use of this technology to cover their tracks and avoid detection. As such, their criminal infrastructures stay up longer to get more victims. These issues are tackled by investigating the dynamics of FFSN by using k-Nearest Neighbor (kNN) classification method and data visualization technique. This combination can assist network administrators and security analyst to recognize the threats more easily and efficiently. In this study, over 500 domains are collected and monitored. By applying kNN classifier to the trained data, the presence of Single-Flux (SF), NS-Flux (NSF), and Double-Flux (DF) are observed. Subsequently, by scrutinizing and visualizing these fluxing domain names, the new types of fluxing designated as NS-Name-Flux(NF) and Nested-NS-Flux (NNF) are discovered. The analysis results of both NF and NNF exposed that FFSN have become extensively sophisticated and dynamic. This exemplifies that visualization is an alternative and effective data exploration method for understanding the complex behaviors of FFSN. 
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650 0 |a Internet  |x Security measures 
650 0 |a Computer networks  |x Security measures 
650 0 |a Information technology  |x Security measures 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Computer Science  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Computer Science 
856 4 |u http://studentrepo.iium.edu.my/handle/123456789/5624 
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