Abstract 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.

Phishing continue to be one of the most drastic attacks causing both financial institutions and customers huge monetary losses. Nowadays mobile devices are widely used to access the Internet and therefore access financial and confidential data. However, unlike PCs and wired devices, such devices lack basic defensive applications to protect against various types of attacks. In consequence, phishing has evolved to target mobile users in Vishing and SMishing attacks recently. This study presents a client-server distributed architecture to detect phishing e-mails by taking advantage of automatic variable selection in Bayesian Additive Regression Trees (BART). When combined with other classifiers, BART improves their predictive accuracy. Further the overall architecture proves to leverage well in resource constrained environments.

Spam is considered an invasion of privacy. Its changeable structures and variability raise the need for new spam classification techniques. The present study proposes using Bayesian additive regression trees (BART) for spam classification and evaluates its performance against other classification methods, including logistic regression, support vector machines, classification and regression trees, neural networks, random forests, and naive Bayes. BART in its original form is not designed for such problems, hence we modify BART and make it applicable to classification problems. We evaluate the classifiers using three spam datasets; Ling-Spam, PU1, and Spambase to determine the predictive accuracy and the false positive rate.

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 built- in 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.

Poor memory management leads to memory leaks, which cause significant performance degradation and failure of software. If ignored, such leaks can potentially cause security breaches and holes in applications. The present study shows that memory leaks can be exploited to cause Denial of Service (DoS) of applications. The ultimate goal of this study is to introduce a security profiling technique that can be used to identify security holes in software. We instrument memory leaks in a Java applet using an open source memory profiler based on Java Virtual Machine Profiler Interface (JVMPI). The results show that it is crucial to perform memory profiling prior to application deployment in order to avoid DoS and vulnerability exploits.

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.