An LSTM based cross-site scripting attack detection scheme for Cloud Computing environments
Abstract Cloud Computing plays a pivotal role in facilitating the Internet of Things (IoT) and its diverse applications. Users frequently access and store data on remote servers in Cloud Computing environments through web browsers. Consequently, attackers may exploit vulnerabilities in web browsing...
Main Authors: | Xiaolong Li, Tingting Wang, Wei Zhang, Xu Niu, Tingyu Zhang, Tengteng Zhao, Yongji Wang, Yufei Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2023-08-01
|
Series: | Journal of Cloud Computing: Advances, Systems and Applications |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13677-023-00483-x |
Similar Items
-
Application Research of BiLSTM in Cross-Site Scripting Detection
by: CHENG Qiqin, WAN Liang
Published: (2020-08-01) -
Detection of Web Cross-Site Scripting (XSS) Attacks
by: Mohammad Alsaffar, et al.
Published: (2022-07-01) -
Short-Term Load Forecasting with an Ensemble Model Based on 1D-UCNN and Bi-LSTM
by: Wenhao Chen, et al.
Published: (2022-10-01) -
Short-Term Load Forecasting Based on Deep Learning Bidirectional LSTM Neural Network
by: Changchun Cai, et al.
Published: (2021-09-01) -
Arrhythmia Classification Based on CNN and Bidirectional LSTM
by: LI Xingxiu, TANG Jianjun, HUA Jing
Published: (2021-12-01)