Semantic Query-Featured Ensemble Learning Model for SQL-Injection Attack Detection in IoT-Ecosystems
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/24/4378406/09625903.pdf?arnumber=9625903
Cited by 27 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Comparison of Multiple Feature Selection Techniques for Machine Learning-Based Detection of IoT Attacks;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30
2. RHM: Novel Graph Convolution Based on Non-Local Network for SQL Injection Identification;2024 IEEE Symposium on Industrial Electronics & Applications (ISIEA);2024-07-06
3. Combining Regular Expressions and Machine Learning for SQL Injection Detection in Urban Computing;Journal of Internet Services and Applications;2024-07-02
4. 5G/6G-enabled metaverse technologies: Taxonomy, applications, and open security challenges with future research directions;Journal of Network and Computer Applications;2024-03
5. Intrusion Detection System to detect impersonation attacks in IoT networks;2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE);2024-01-24
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