Modeling and Analysis of Intentional And Unintentional Security Vulnerabilities in a Mobile Platform Page: 53
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their analysis indicate that: i) even in case of popular photographs, information does not spread
widely throughout the network, ii) it spreads slowly, and iii) information exchange between friends
accounts for over 50% of all favorite markings, and it incurs a significant delay at each hop.
In a work on SN content analysis, [63] employ ISIS, a general stochastic model (with a set
of sequential statistical tests) for Interacting Streaming Information Sources, to identify items that
gather a higher attention in social media. In a similar application context, [19] identify messages
dealing with the trending topics or special events in an SN using visualization techniques and
artificial intelligence based data mining methods.
In the context of new challenges in this field related to privacy, background knowledge, and
data utility, many researchers addressed the anonymization (user identity suppression) problem.
[110] present a short but systematic review of the existing anonymization techniques for privacy
preserving publishing of social network data. Considering trust between users in a social network
as a parameter similar to the reputation of a specified user rather than a quantification of preference
and profile matches between users, [53] propose a fuzzy logic based system to compute the trust
values for individual users in an SN by propagation and aggregation through the network the trust
values provided on a scale of 0 to 10 by the users about the other directly connected (hence well
known) users. [57] address the problem of detection of spam among blogs, the SN media similar to
a micro blogger like Twitter, but with more capability. The authors basically identify the spammers
from the repetitive temporal regularity of contents and consistent linking patterns. The temporal
regularity, in turn, is measured by using the entropy of the "blog post time" difference distribution.
Experimental results indicate that a high accuracy of 90% in spam blog detection can be achieved
by their method. [102] address the problem of identification of influential users in twitter using
an improved page-ranking system called TwitterRank based on the concept of homophily, the
tendency of individuals to associate and link with similar others, or those with similar topics of
interests.
In the context of SN privacy, I address in this dissertation the problem of identification of
types users in a twitter network. I categorize the twitter users into 4 types: i) Leaders (those like
the news groups, who start tweeting, but do not follow any one there after, though they could have53
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Mohamed Issadeen, Mohamed Fazeen. Modeling and Analysis of Intentional And Unintentional Security Vulnerabilities in a Mobile Platform, dissertation, December 2014; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc700067/m1/67/: accessed July 18, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .