@inproceedings{643cf246571a4c66a809ad0e1cf8f251,
title = "Measuring the Potential for Victimization in Malicious Content",
abstract = "Sending malicious content to users for obtaining personnel, financial, or intellectual property has become a multi-billion dollar criminal enterprise. This content is primarily presented in the form of emails, social media posts, and phishing websites. User training initiatives seek to minimize the impact of malicious content through improved vigilance. Training works best when tailored to specific user deficiencies. However, tailoring training requires understanding how malicious content victimizes users. In this paper, we link a set of malicious content design factors, in the form of degradations and sophistications, to their potential to form a victimization prediction metric. The design factors examined are developed from an analysis of over 100 pieces of content from email, social media and websites. We conducted an experiment using a sample of the content and a game-based simulation platform to evaluate the efficacy of our victimization prediction metric. The experimental results and their analysis are presented as part of the evaluation.",
keywords = "content assessment, maliciousness, metrics, phishing, trust, trust factors, user training, victimization",
author = "Hale, {Matthew L.} and R. Gamble and J. Hale and M. Haney and J. Lin and C. Walter",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Web Services, ICWS 2015 ; Conference date: 27-06-2015 Through 02-07-2015",
year = "2015",
month = aug,
day = "13",
doi = "10.1109/ICWS.2015.49",
language = "English (US)",
series = "Proceedings - 2015 IEEE International Conference on Web Services, ICWS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "305--312",
editor = "Miller, {John A.} and Hong Zhu",
booktitle = "Proceedings - 2015 IEEE International Conference on Web Services, ICWS 2015",
}