This project contains dataset for Cross Site Scripting(XSS). The project contains the Matlab code for creating SVM, K-NN, Random Forest, and Neural Networks classifiers to detect Web applications attacks.
If f you would like to cite the datasets or code, please use the following references:
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Mereani, F. A. and Howe, J. M. (2018). Detecting Cross-Site Scripting Attacks Using Machine Learning. In Advanced Machine Learning Technologies and Applications, volume 723 of AISC, pages 200–210. Springer.
Link: https://link.springer.com/chapter/10.1007/978-3-319-74690-6_20 -
Mereani, F. A. and Howe, J. M. (2018). Preventing Cross-Site Scripting Attacks by Combining Classifiers. In Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1, pages 135–143. SciTePress.
Link: https://www.scitepress.org/Link.aspx?doi=10.5220/0006894901350143 -
Mereani., F. A. and Howe., J. M. (2019). Exact and approximate rule extraction from neural networks with boolean features. In Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019), pages 424–433. INSTICC, SciTePress.T
Link: https://www.scitepress.org/Link.aspx?doi=10.5220/0008362904240433