Enhancing SQL Query Security using Graph-based Hierarchical Embeddings with SMOTE and Advanced Neural Networks for Robust Detection

SQL Injection Attacks (SQLIA) are still a significant security vulnerability, targeting issues in database query validation for intruder access. The research proposes a graph-based hierarchical embedding framework for SQLIA detection using Abstract Syntax Trees (ASTs) and spectral graph theory to id...

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Vydané v:	2025 12th International Conference on Computing for Sustainable Global Development (INDIACom) s. 1 - 7
Hlavní autori:	K, Mangaiyarkarasi, P. S., Uma Priyadarsini
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Bharati Vidyapeeth, New Delhi 02.04.2025
Predmet:	Accuracy Anomaly detection Forestry Graph Embeddings Neural Networks Noise measurement Outlier Detection Real-time systems Security Semantics SMOTE SQL injection SQL Injection Attack Syntactics
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