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An Integrated Intelligent Approach to Enhance the Security Control of IT Systems. A Proactive Approach to Security Control Using Artificial Fuzzy Logic to Strengthen the Authentication Process and Reduce the Risk of Phishing
Salem, Omran S.A.
Salem, Omran S.A.
Publication Date
2012
End of Embargo
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The University of Bradford theses are licenced under a Creative Commons Licence.
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Institution
University of Bradford
Department
Faculty of Engineering and Informatics, School of Electrical Engineering and Computer Science
Awarded
2012
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Abstract
Hacking information systems is continuously on the increase. Social engineering
attacks is performed by manipulating the weakest link in the security chain; people.
Consequently, this type of attack has gained a higher rate of success than a technical
attack.
Based in Expert Systems, this study proposes a proactive and integrated
Intelligent Social Engineering Security Model to mitigate the human risk and reduce the
impact of social engineering attacks.
Many computer users do not have enough security knowledge to be able to
select a strong password for their authentication. The author has attempted to implement
a novel quantitative approach to achieve strong passwords. A new fuzzy logic tool is
being developed to evaluate password strength and measures the password strength
based on dictionary attack, time crack and shoulder surfing attack (social engineering).
A comparative study of existing tools used by major companies such as Microsoft,
Google, CertainKey, Yahoo and Facebook are used to validate the proposed model and
tool.
A comprehensive literature survey and analytical study performed on phishing
emails representing social engineering attacks that are directly related to financial fraud
are presented and compared with other security threats. This research proposes a novel
approach that successfully addresses social engineering attacks. Another intelligent tool
is developed to discover phishing messages and provide educational feedback to the user focusing on the visible part of the incoming emails, considering the email’s source
code and providing an in-line awareness security feedback.
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Type
Thesis
Qualification name
PhD