Detection of SQL injection attacks
Web applications that employ SQL datasets are at serious risk from SQL injection attacks. Using two separate datasets, this study examined the utility of ML classification approaches for identifying SQL injection threats. On two datasets—one taken from the actual world and the other created artificially—random forest (RF), descion tree (DT), k-nearest ...
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Machine-Learning-Based Detection of SQL Injection Attacks in Web Applications
The increasing development and prevalence of web applications have contributed to a surge in web attacks, with injection vulnerabilities considered amongst the most pivotal, widespread, and severe.
Haya Aldossary, Noura Aleisa
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Deep Learning in Cybersecurity: A Hybrid BERT–LSTM Network for SQL Injection Attack Detection
In the past decade, cybersecurity has become increasingly significant, driven largely by the increase in cybersecurity threats. Among these threats, SQL injection attacks stand out as a particularly common method of cyber attack.
Yixian Liu, Yupeng Dai
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A Hybrid Deep Learning Model for SQL Injection Attack Detection
An increasing number of web application services raises significant security concerns. Online access to these applications exposes them to multiple cyberattacks.
Emanuel N. Casmiry +2 more
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Labelled IoT flow-based network traffic dataset for cyberattack detection. [PDF]
Martínez B +4 more
europepmc +1 more source
Enhanced SQL injection detection using chi-square feature selection and machine learning classifiers. [PDF]
Casmiry E, Mduma N, Sinde R.
europepmc +1 more source
SafeCodeRL: Security-Constrained Multi-Agent Reinforcement Learning for Trustworthy LLM-Generated IoT/CPS Software. [PDF]
Wang Z, Chen J, Wei Z, Lin L, Tong G.
europepmc +1 more source
SentinelSphere: An AI-driven cybersecurity platform integrating real-time threat detection with security awareness education. [PDF]
Tantaroudas ND +2 more
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Web application firewall based on machine learning models. [PDF]
Durmuşkaya ME, Bayraklı S.
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