Wednesday 24 October 2012

REFRENCES
[1] G. A. Di Lucca, A. R. Fasolino, M. Mastoianni, P. Tramontana,
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[2] Shanmugam, Jayamsakthi (BITS); Ponnavaikko, “A solution to block
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[3] Alcorn, Wade, “Cross-site scripting viruses and worms - a new attack
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[4] White Hat Securtiy, “Cross Site Scripting worms and viruses, The
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org/dl/articles/WHXSSThreats.pdf.
0 20 40 60 80 100 120 140 160 180 200
0
5000
10000
15000
Time
Total Number of Infected Profiles
Simulation
Analytical
Simulation
Analytical
q=.1
q=.9
0 20 40 60 80 100 120 140 160 180 200
0
5000
10000
15000
Time Total Number of Infected Profiles
q = .1
q = .5
q = .7
q = .9
0 20 40 60 80 100 120 140 160 180 200
0
5000
10000
15000
Time
Total Number of Infected Profiles
q = .1
q = .5
q = .7
q = .9
100 101 102 103 104 10-5
10-4
10-3
10-2
10-1
100
Friends
Numbers
[5] Gary Wassermann, Zhendong Su, “Static detection of cross-site scripting
vulnerabilities”, Proceedings of the 30th international conference on
Software engineering, ICSE '08, Leipzig, Germany. 2008
[6] The Samy Worm, “I'll never get caught. I'm Popular.”.R. M. Anderson,
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[8] H. Andersson, T. Britton. “Stochastic Epidemic Models and Their
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[9] N. T. Bailey. “The Mathematical Theory of Infectious Diseases and its
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[10] J. C. Frauenthal. “Mathematical Modeling inEpidemiology. Springer-
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[11] Kermack, W. and McKendrick, “A contribution to the mathematical
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[12] Thelwall, Mike, “Social networks, gender, and friending: An analysis of
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[13] Fogel, J. & Nehmad, E. Internet “social network communities Risk
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[14] Zou, Cliff Changchun , “Code red worm propagation modeling and
analysis”, roceedings of the ACM Conference on Computer and
Communications Security, 2002, p 138-147
[15] Bulygin, Y, “Epidemics of Mobile Worms”, Performance, Computing,
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[16] Ralph Gross, Alessandro Acquisti, H. John Heinz, III, “Information
revelation and privacy in online social networks”, Proceedings of the
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[17] Barabási, Albert-László and Réka Albert, "Emergence of scaling in
random networks", Science, 286:509-512, October 15, 1999.

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