Phinding Phish: An Evaluation of Anti-Phishing Toolbars

By Lorrie Faith Cranor, Serge Egelman, Jason I. Hong, Yue Zhang. 2007

286 citations recorded by the source corpus.

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Citations in the corpus

PhishEye: Live Monitoring of Sandboxed Phishing Kits (2016, background): “1% of the market of Internet browsers(3), and second because PhishTank has been extensively used as a source feed in many previous research studies [44, 29, 26].”
Anti-Phishing Phil: the design and evaluation of a game that teaches people not to fall for phish (2007, background): “In a recent study, only one of the ten anti-phishing tools tested was able to correctly identify over 90% of phishing web sites, and that tool also incorrectly identified 42% of legitimate web sites as fraudulent [39].”
An Empirical Analysis of Phishing Blacklists (2009, methodology): “also used this technique to gather their samples [38].”
Examining the impact of website take-down on phishing (2007, background): “Categories and Subject Descriptors K.4.4 [Computing Milieux]: Computers and Society Electronic Commerce, Security Keywords phishing, security economics, electronic crime 1.”
Behind Phishing: An Examination of Phisher Modi Operandi (2008, background): “Cranor et al.[4] analyzed the efﬁcacy of toolbars in identifying phishing sites.”
There Is No Free Phish: An Analysis of "Free" and Live Phishing Kits (2008, methodology): “The detection of spoofed web sites has also received considerable attention, and various techniques have been proposed, based, for example, on the measurement of visual similarity between web pages [31], anomaly detection techniques [22], or information retrieval approaches [35].”
On the Effectiveness of Techniques to Detect Phishing Sites (2007, background): “Also, independently and concurrently from our work, Zhang et al. [33] have also performed a similar study that investigates the efficiency of anti-phishing solutions.”
You're Not Who You Claim to Be: Website Identity Check for Phishing Detection (2010, background): “Classification-based approaches consider not only URL but also various features in the content of the given website and have shown great promises in many systems [20], [21], [7], [9], [6], [19].”
A framework for detection and measurement of phishing attacks (2007, background): “Recently, Zhang et al. [ 25 ] conducted a thorough analysis on several anti-phishing tool bars to evaluate their effectiveness.”
A comparison of machine learning techniques for phishing detection (2007, background): “In another study [10], the authors tested the eﬀectiveness of 10 security toolbars and found that three of the 10 tool-bars were able to identify over 75% of the phishing sites tested.”
You've been warned: an empirical study of the effectiveness of web browser phishing warnings (2008, background): “Unfortunately, a recent study on anti-phishing toolbar accuracy found that these tools fail to identify a substantial proportion of phishing websites [26].”
Cantina: a content-based approach to detecting phishing web sites (2007, methodology): “In our previous studies Netcraft’s performance varied from test to test, ranging from 75% to 96% of phishing sites detected [6].”