WebGuardRL: An Innovative Reinforcement Learning-based Approach for Advanced Web Attack Detection
Abstract
References
Index Terms
- WebGuardRL: An Innovative Reinforcement Learning-based Approach for Advanced Web Attack Detection
Recommendations
XSS adversarial example attacks based on deep reinforcement learning
AbstractCross-site scripting (XSS) attack is one of the most serious security problems in web applications. Although deep neural network (DNN) has been used in XSS attack detection and achieved unprecedented success, it is vulnerable to ...
Reducing errors in the anomaly-based detection of web-based attacks through the combined analysis of web requests and SQL queries
Best papers of the Sec Track at the 2006 ACM SymposiumWeb-based applications have become a popular means of exposing functionality to large numbers of users by leveraging the services provided by web servers and databases. The wide proliferation of custom-developed web-based applications suggests that ...
Towards DDoS attack detection using deep learning approach
AbstractDue to the extensive use and evolution in the cyber world, different network attacks have recently increased significantly. Distributed Denial-of-Service (DDoS) attack has become one of the fatal threats to the Internet, where attackers send ...
Comments
Information & Contributors
Information
Published In
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 52Total Downloads
- Downloads (Last 12 months)52
- Downloads (Last 6 weeks)4
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format