The battle against phishing: Dynamic Security Skins

By Rachna Dhamija, J. Doug Tygar. 2005

574 citations recorded by the source corpus.

Subfields: Information Systems, Signal Processing

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Citations in the corpus

PhishEye: Live Monitoring of Sandboxed Phishing Kits (2016, background): “Several studies propose a browser plugin to protect users from phishing [6, 9, 20].”
Detecting visually similar Web pages: Application to phishing detection (2010, unknown): “Some well-known mutual authentication solutions include DSS [Dhamija and Tygar 2005], PassMark (now part of the RSA Identity Protection & Veri.cation Suite) [RSA 2009], and YahooMail s sign-in seals (Yahoo 2009].”
Detecting Phishing Web Pages with Visual Similarity Assessment Based on Earth Mover's Distance (EMD) (2006, methodology): “The most popular and major antiphishing methods include authentication, which includes e-mail authentication and Web page authentication (e.g., [21]), filtering, which includes e-mail filtering and Web page filtering, attack analyzing and tracing, immune-system-like phishing report and detection,…”
An Empirical Analysis of Phishing Blacklists (2009, background): “[8, 36, 31, 37]) are needed to overcome the initial limited blacklist coverage problem.”
Do security toolbars actually prevent phishing attacks? (2006, background): “Dynamic Security Skins [ 6] proposes to use a randomly generated visual hash to customize the browser window or web form elements to indicate the successfully authenticated sites.”
Anomaly Based Web Phishing Page Detection (2006, background): “For instance, Dynamic Security Skins [5] [6] allows a remote server to prove its identity in the form of an image which is unique for each user and each transaction such that users visually verify whether the image from the server matches its corresponding local image .”
Why phishing works (2006, background): “To address some of these issues, we have designed and are currently testing a new approach that allows a remote server to prove its identity in a way that is easy for a user to verify (exploiting the human ability to easily match images) but difficult for an attacker to spoof [7].”
A framework for detection and measurement of phishing attacks (2007, methodology): “The battle against phishing: Dynamic Security Skins.”
So long, and no thanks for the externalities: the rational rejection of security advice by users (2009, background): “Whitten and Tygar [24] .nd that most users are unable to successfully navigate an encryption software package.”
Protecting people from phishing: the design and evaluation of an embedded training email system (2007, background): “Ye and Sean [39] and Dhamija and Tygar [8] have developed prototype “trusted paths” for the Mozilla web browser that are designed to assist users in verifying that their browser has made a secure connection to a trusted site.”