Over the last few years, web-based attacks have caused significant harm to users. Many of these attacks occur through the exploitations of common security vulnerabilities in web-based programs. Given that, mitigation of these attacks is extremely crucial to reduce some of the harmful consequences. Web-based applications contain vulnerabilities that can be exploited by attackers at a client-side (browser) without the victim’s (browser user’s) knowledge. This thesis is intended to mitigate some exploitations due to the presence of security vulnerabilities in web applications while performing seemingly benign functionalities at the client-side. For example, visiting a webpage might result in JavaScript code execution (cross-site scripting), downloading a file might lead to the execution of JavaScript code (content sniffing), clicking on a hyperlink might result in sending unwanted legitimate requests to a trusted website (cross-site request forgery), and filling out a seemingly legitimate form may eventually lead to stealing of credential information (phishing). Existing web-based attack detection approaches suffer from several limitations such as (i) modification of both server and client-side environments, (ii) exchange of sensitive information between the server and client, and (iii) lack of detection of some attack types. This thesis addresses these limitations by mitigating four security vulnerabilities in web applications: cross-site scripting, content sniffing, cross-site request forgery, and phishing. We mitigate the exploitations of these vulnerabilities by developing automatic attack detection approaches at both server and client-sides. We develop server-side attack detection frameworks to detect attack symptoms within response pages before sending them to the client. The approaches are designed based on the assumption that the server-side program source is available for analysis, but we are not allowed to alter the program code and the runtime environments. Moreover, we develop client-side attack detection frameworks so that some level of protection is present when the source code of server websites (either trusted or untrusted) is not available. Our proposed solutions explore several techniques such as response page parsing and file content analysis, browser-level checking of requests and responses, and finite state machine-based behavior monitoring. The thesis evaluates the proposed attack detection approaches with real-world vulnerable programs. The evaluation results indicate that our approaches are effective and perform better than the related work. We also contribute to the development of benchmark suites for evaluating attack detection techniques. / Thesis (Ph.D, Computing) -- Queen's University, 2011-11-29 09:44:24.465