Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.738151
Title: 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
Author: Salem, Omran S. A.
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.738151  DOI: Not available
Keywords: Information security ; Authentication ; Email phishing ; Security awareness ; Fuzzy logic ; Social engineering attacks ; Password strength
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