Sep 23, 2024 · In this study, a suite of integrated machine learning and deep learning models is designed to detect web attacks.

E-WebGuard: Enhanced neural architectures for precision web attack detection ... Anomaly-based web attack detection: a deep learning approach. In ...

A novel approach for securing web applications from both cross-site scripting attacks and SQL injection attacks using decoding and standardization of SQL ...

在二元分类任务中，采用线性核的Char-SVM 模型优于其他模型，准确率达到99.60%。CNN-Bi-LSTM 模型紧随其后，准确率达到99.41%，超过了之前研究中CNN-LSTM 模型的表现。在多 ...

Publications (2). E-WebGuard: Enhanced neural architectures for precision web attack detection · Article. September 2024. ·. 7 Reads. Computers & Security.

E-WebGuard: Enhanced neural architectures for precision web attack detection. Web applications have become a favored tool for organizations to disseminate ...

(2025)E-WebGuard: Enhanced neural architectures for precision web attack detection ... Index Terms. Anomaly-Based Web Attack Detection: A Deep Learning Approach.

E-WebGuard: Enhanced neural architectures for precision web attack detection ... HMM-Web: A Framework for the Detection of Attacks Against Web Applications.

This work investigates the use of deep learning techniques to improve the performance of web application firewalls (WAFs), systems that are used to detect ...

[2024/09] Congratulations! New paper, "E-WebGuard: Enhanced Neural Architectures for Precision Web Attack Detection", accepted by Computers & Security, first ...