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The increasing demand to develop a palmprint biometric system with a low-error rate has prompted scientists to use multispectral imaging to overcome the limits of the techniques that act in visible light. In order to improve the accuracy of multispectral palmprint recognition, we explore two level fusions: pixel and the feature level fusion approaches. The former is based on a maximum selection rule, which combines discriminating information from different spectral bands of discrete wavelet transform of multispectral images. The latter operates the fusion of features extracted from subimages. We propose to use both approaches for statistical and energy distribution analysis of the finite ridgelet transform coefficients, for the sake of their simplicity and low-computational complexity. Once the feature vectors are obtained, we perform a robust classification to identify/verify individuals with both approaches. The effectiveness of the proposed methods is evaluated on several classifiers for binary and multiclass cases. The experimental results conducted on Chinese Academy of Sciences Institute of Automation and Hong Kong Polytechnic University databases show that the proposed approaches ensure, respectively, an accuracy rate of 100% and 99.79%. A comparative study has revealed that our approach outperforms or at least equals the performances of the state-of-the-art multispectral palmprint recognition methods. Bouchemha et al.: Multispectral palmprint recognition methodology based on multiscale representation Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 08/03/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Journal of Electronic Imaging 043005-3 Jul∕Aug 2015 • Vol. 24(4) Bouchemha et al.: Multispectral palmprint recognition methodology based on multiscale representation Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 08/03/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Amel Bouchemha received her engineer degree in electrical engineering from University of Constantine in 1992, then her DEA degree in signal processing. In 1999, she received her magister degree from the University of Constantine. Since 2001, she has been working as a researcher and associate professor at the University of Tebessa, Algeria. Her principal research interests include biometric, signal processing, image processing, modeling, and fault detection. Bouchemha et al.: Multispectral palmprint recognition methodology based on multiscale representation Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 08/03/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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Cross-site scripting (XSS) is one of the major threats menacing the privacy of data and the navigation of trusted web applications. Since its reveal in late 1999 by Microsoft security engineers, several techniques have been developed in the aim to secure web navigation and protect web applications against XSS attacks. The problem became worse with the emergence of advanced web technologies such as Web services and APIs and new programming styles such as AJAX, CSS3 and HTML5. While new technologies enable complex interactions and data exchanges between clients and servers in the network, new programming styles introduce new and complicate injection flaws to web applications. XSS has been and still in the TOP 10 list of web vulnerabilities reported by the Open Web Applications Security Project (OWASP). Consequently, handling XSS attacks became one of the major concerns of several web security communities. In this paper, we contribute by conducting a systematic mapping and a comprehensive survey. We summarize and categorize existent endeavors that aim to protect against XSS attacks and develop XSS-free web applications. The present review covers 147 high quality published studies since 1999 including early publications of 2022. A comprehensive taxonomy is drawn out describing the different techniques used to prevent, detect, protect and defend against XSS attacks. Although the diversity of XSS attack types and the scripting languages that can be used to state them, the systematic mapping revealed a remarkable bias toward basic and JavaScript XSS attacks and a dearth of vulnerability repair mechanisms. The survey highlighted the limitations, discussed the potentials of existing XSS attack defense mechanisms and identified potential gaps.

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