There are many applications available for phishing detection. However, unlike predicting spam, there are only few studies that compare machine learning techniques in predicting phishing. The present study compares the predictive accuracy of several machine learning methods including Logistic Regression (LR), Classification and Regression Trees (CART), Bayesian Additive Regression Trees (BART), Support Vector Machines (SVM), Random Forests (RF), and Neural Networks (NNet) for predicting phishing emails. A data set of 2889 phishing and legitimate emails is used in the comparative study. In addition, 43 features are used to train and test the classifiers.

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One of the solutions that has been widely used by naive users to protect against phishing attacks is security toolbars or phishing filters in web browsers. The present study proposes a new attack to bypass security toolbars and phishing filters via local DNS poisoning without the need of an infection vector. A rogue wireless access point (AP) is set up, poisoned DNS cache entries are used to forge the results provided to security toolbars, and thus misleading information is displayed to the victim. Although there are several studies that demonstrate DNS poisoning attacks, none to our best knowledge investigate whether such attacks can circumvent security toolbars or phishing filters. Five well‐known security toolbars and three reputable browser built‐in phishing filters are scrutinized, and none of them detect the attack. So ineptly, security toolbars provide the victim with false confirmative indicators that the phishing site is legitimate. Copyright © 2009 John Wiley & Sons, Ltd.

Stress-testing has been widely used by businesses, governments, and other organizations to evaluate the strength of their web applications against various attacks. However, the quality of these tests is under constant scrutiny to determine their effectiveness. The present study compares four stress-testing tools, by performing the tests on two major web-based applications. All of the tools used are open source, and run on Win32 platform. The test scenarios are recorded from server log files to make the tests more realistic. Lastly, we discuss how to use stress-testing tools as a measure to avoid Denial of Service attacks on web servers and web applications.

Security toolbars are used to protect naive users against phishing attacks by displaying warnings on suspicious sites. Recently, web browsers have added built-in phishing filters mimicking the same functionality to detect phishing sites. The present study proposes a new attack to bypass security toolbars and phishing filters via DNS poisoning. Spoofed DNS cache entries are used to forge the results provided to security toolbars and thus misleading information is displayed to the victim. Although there are several studies that demonstrate DNS poisoning attacks, none to our best knowledge, investigate whether such attacks can circumvent security toolbars or phishing filters. Four well-known security toolbars and three reputable browser builtin phishing filters are scrutinized. None of the seven tools detect the attack. Worse still, security toolbars provide the victim with false confirmative indicators that the phishing site is legitimate.