期刊名称：Journal of Intelligent Learning Systems and Applications
印刷版ISSN：2150-8402
电子版ISSN：2150-8410
出版年度：2012
卷号：4
期号：4
页码：319-329
DOI：10.4236/jilsa.2012.44033
出版社：Scientific Research Publishing
摘要：This paper analyzes users’ trust decision patterns for detecting phishing sites. Our previous work proposed HumanBoost [1] which improves the accuracy of detecting phishing sites by using users’ Past Trust Decisions (PTDs). Web users are generally required to make trust decisions whenever their personal information is requested by a website. Human-Boostassumed that a database of Web user’s PTD would be transformed into a binary vector, representing phishing or not-phishing, and the binary vector can be used for detecting phishing sites, similar to the existing heuristics. Here, this paper explores the types of the users whose PTDs are useful by running a subject experiment, where 309 participants- browsed 40 websites, judged whether the site appeared to be a phishing site, and described the criterion while assessing the credibility of the site. Based on the result of the experiment, this paper classifies the participants into eight groups by clustering approach and evaluates the detection accuracy for each group. It then clarifies the types of the users who can make suitable trust decisions for HumanBoost.
关键词：Detection of Phishing Sites; Trust Decision; Credibility of Websites; Machine Learning; Cluster Analysis
