M. Hale, R. Gamble, John Hale, Charles Haney, Jessica Lin, Charles Walter
{"title":"Measuring the Potential for Victimization in Malicious Content","authors":"M. Hale, R. Gamble, John Hale, Charles Haney, Jessica Lin, Charles Walter","doi":"10.1109/ICWS.2015.49","DOIUrl":null,"url":null,"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.","PeriodicalId":250871,"journal":{"name":"2015 IEEE International Conference on Web Services","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Web Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWS.2015.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
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.