Date of Award
Doctor of Philosophy (PhD)
College of Computing and Engineering
James R. Kiper
Martha M. Snyder
Millions of people willingly expose their lives via Internet technologies every day, and even the very few ones who refrain from the use of the Internet find themselves exposed through data breaches. Billions of private information records are exposed through the Internet. Marketers gather personal preferences to influence shopping behavior. Providers gather personal information to deliver enhanced services, and underground hacker networks contain repositories of immense data sets. Few users of Internet technologies have considered where their information is going or who has access to it. Even fewer are aware of how decisions made in their own lives expose significant pieces of information, which can be used by cyber hackers to harm the very organizations with whom they are affiliated. While this threat can affect any person holding any position at an organization, upper management poses a significantly higher risk due to their level of access to critical data and finances targeted by cybercrime.
The goal of this research was to develop and validate a Social Engineering eXposure Index (SEXI)™ using Open-Source Personal Information (OSPI) to assist in identifying and classifying social engineering vulnerabilities. This study combined an expert panel using the Delphi method, developmental research, and quantitative data collection. The expert panel categorized and assessed information privacy components into three identifiability groups, subsequently used to develop an algorithm that formed the basis for a SEXI. Validation of the algorithm used open-source personal information found on the Internet for 50 executives of Fortune 500 organizations and 50 Hollywood celebrities. The exposure of each executive and persona was quantified and the collected data were evaluated, analyzed, and presented in an anonymous aggregated form.
Phase 1 of this study developed and evaluated the SEXI benchmarking instrument via an expert panel using the Delphi expert methodology. During the first round, 3,531 data points were collected with 1,530 having to do with the demographics, qualifications, experience, and working environments of the panel members as well as 2,001 attributing levels of exposure to personal information. The second Delphi round presented the panel members with the feedback of the first-round tasking them with categorizing personal information, resulting in 1,816 data points. Phase 2 of this study used the composition, weights, and categories of personal information from Phase 1 in the development of a preliminary SEXI benchmarking instrument comprised of 105 personal information items. Simulated data was used to validate the instrument prior to the data collection. Before initiating Phase 3, the preliminary SEXI benchmarking instrument was fully tested to verify the accuracy of recorded data. Phase 3 began with discovering, evaluating, and validating repositories of publicly available data sources of personal information. Approximately two dozen sources were used to collect 11,800 data points with the SEXI benchmarking index. Upon completion of Phase 3, data analysis of the Fortune 500 executives and Hollywood personas used to validate the SEXI benchmarking index.
Data analysis was conducted in Phase 3 by one-way Analysis of Variance (ANOVA). The results of the ANOVA data analysis from Phase 3 revealed that age, gender, marital status, and military/police experience were not significant in showing SEXI differences. Additionally, income, estimated worth, industry, organization position, philanthropic contributions are significant, showing differences in SEXI. The most significant differences in SEXI in this research study were found with writers and chief information officers. A t-test was performed to compare the Fortune 500 executives and the Hollywood personas. The results of the t-test data analysis showed a significant difference between the two groups in that Hollywood Personas had a higher SEXI than the Fortune 500 Executives suggesting increased exposure due to OSPI.
The results of this research study established, categorized, and validated a quantifiable measurement of personal information. Moreover, the results of this research study validated that the SEXI benchmarking index could be used to assess an individual’s exposure to social engineering due to publicly available personal information. As organizations and public figures rely on Internet technologies understanding the level of personal information exposure is critical is protecting against social engineering attacks. Furthermore, assessing personal information exposure could provide an organization insight into exposed personal information facilitating further mitigation of threats or potential social engineering attack vectors. Discussions and implications for future research are provided.
William Shawn Wilkerson. 2021. Development of a Social Engineering eXposure Index (SEXI) using Open-Source Personal Information. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Computing and Engineering. (1162)