Biblio
This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the γ-filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time series prediction, complex nonlinear system identification, and adaptive antenna array processing demonstrate the potential of the approach for scenarios where recursivity and nonlinearity have to be readily combined.
Due to the frequent usage of online web applications for various day-to-day activities, web applications are becoming most suitable target for attackers. Cross-Site Scripting also known as XSS attack, one of the most prominent defacing web based attack which can lead to compromise of whole browser rather than just the actual web application, from which attack has originated. Securing web applications using server side solutions is not profitable as developers are not necessarily security aware. Therefore, browser vendors have tried to evolve client side filters to defend against these attacks. This paper shows that even the foremost prevailing XSS filters deployed by latest versions of most widely used web browsers do not provide appropriate defense. We evaluate three browsers - Internet Explorer 11, Google Chrome 32, and Mozilla Firefox 27 for reflected XSS attack against different type of vulnerabilities. We find that none of above is completely able to defend against all possible type of reflected XSS vulnerabilities. Further, we evaluate Firefox after installing an add-on named XSS-Me, which is widely used for testing the reflected XSS vulnerabilities. Experimental results show that this client side solution can shield against greater percentage of vulnerabilities than other browsers. It is witnessed to be more propitious if this add-on is integrated inside the browser instead being enforced as an extension.
Cross-Site Scripting (XSS) is a common attack technique that lets attackers insert the code in the output application of web page which is referred to the web browser of visitor and then the inserted code executes automatically and steals the sensitive information. In order to prevent the users from XSS attack, many client- side solutions have been implemented; most of them being used are the filters that sanitize the malicious input. However, many of these filters do not provide prevention to the newly designed sophisticated attacks such as multiple points of injection, injection into script etc. This paper proposes and implements an approach based on encoding unfiltered reflections for detecting vulnerable web applications which can be exploited using above mentioned sophisticated attacks. Results prove that the proposed approach provides accurate higher detection rate of exploits. In addition to this, an implementation of blocking the execution of malicious scripts have contributed to XSS-Me: an open source Mozilla Firefox security extension that detects for reflected XSS vulnerabilities which can be considered as an effective solution if it is integrated inside the browser rather than being enforced as an extension.