Information manipulation for deception continues to evolve at a remarkable rate. Artificial intelligence has greatly reduced the burden of combing through documents for evidence of manipulation; but it has also enabled the development of clever modes of deception. In this study, we modeled deception attacks by examining phishing emails that successfully evaded detection by the Microsoft 365 filtering system. The sample population selected for this study was the University of North Texas students, faculty, staff, alumni and retirees who maintain their university email accounts. The model explains why certain individuals and organizations are selected as targets, and identifies potential counter measures and counter attacks. Over a one-year period, 432 phishing emails with different features, characters, length, context and semantics successfully passed through Microsoft Office 365 filtering system. The targeted population ranged from 18 years old up to those of retirement age; ranged across educational levels from undergraduate through doctoral levels; and ranged across races. The unstructured data was preprocessed by filtering out duplicates to avoid overemphasizing a single attack. The term frequency-inverse document frequency (TF-IDF) and distribution of words over documents (topic modeling) were analyzed. Results show that staff and students were the main target audience, and the phishing email volume spiked in the summer and holiday season. The TF-IDF analysis showed that the phishing emails could be categorized under six categories: reward, urgency, job, entertainment, fear, and curiosity. Analysis showed that attackers use information gap theory to bait email recipients to open phishing emails with no subject line or very attractive subject line in about thirty percent of cases. Ambiguity remains the main stimulus used by phishing attackers, while the reinforcements used to misinform the targets range from positive reinforcements (prize, reward) to negative reinforcements (blackmail, potential consequences).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.