@misc{owasp2021,
  author = {{OWASP Foundation}},
  title  = {{OWASP Top 10: 2021 -- The Ten Most Critical Web Application Security Risks}},
  year   = {2021},
  url    = {https://owasp.org/Top10/},
  note   = {Accessed: Nov.~2025}
}

@misc{cve25257,
  author = {{National Vulnerability Database}},
  title  = {{CVE-2025-25257 Detail}},
  year   = {2025},
  url    = {https://nvd.nist.gov/vuln/detail/CVE-2025-25257}
}

@misc{cve1094,
  author = {{National Vulnerability Database}},
  title  = {{CVE-2025-1094 Detail}},
  year   = {2025},
  url    = {https://nvd.nist.gov/vuln/detail/CVE-2025-1094}
}

@misc{cve22974,
  author = {{National Vulnerability Database}},
  title  = {{CVE-2025-22974 Detail}},
  year   = {2025},
  url    = {https://nvd.nist.gov/vuln/detail/CVE-2025-22974}
}

@article{balogun2025,
  author  = {Balogun, Semirat Abidemi and Ijiga, Onuh Matthew and Okika, Nonso and Enyejo, Lawrence Anebi and Ogboji, James Agbo},
  title   = {Machine Learning-Based Detection of SQL Injection and Data Exfiltration Through Behavioral Profiling of Relational Query Patterns},
  journal = {International Journal of Innovative Science and Research Technology},
  volume  = {10},
  number  = {8},
  pages   = {49--63},
  year    = {2025},
  doi     = {10.38124/ijisrt/25aug324},
}

@article{rawat2012svm,
  author  = {Rawat, Romil and Shrivastav, Shailendra Kumar},
  title   = {SQL Injection Attack Detection Using SVM},
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  year    = {2012},
  doi     = {10.5120/5749-7043},
}

@inproceedings{kumar2012survey,
  author    = {Kumar, P. and Pateriya, R. K.},
  title     = {A Survey on SQL Injection Attacks, Detection and Prevention Techniques},
  booktitle = {2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT)},
  pages     = {1--5},
  year      = {2012},
  doi       = {10.1109/ICCCNT.2012.6396096},
  publisher = {IEEE}
}

@article{lee2012novel,
  author  = {Lee, Inyong and Jeong, Soonki and Yeo, Sangsoo and Moon, Jongsub},
  title   = {A Novel Method for SQL Injection Attack Detection Based on Removing SQL Query Attribute Values},
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  volume  = {55},
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}

@article{lo2025lightweight,
  author  = {Lo, Rui-Teng and Hwang, Wen-Jyi and Tai, Tsung-Ming},
  title   = {SQL Injection Detection Based on Lightweight Multi-Head Self-Attention},
  journal = {Applied Sciences},
  volume  = {15},
  number  = {2},
  pages   = {571},
  year    = {2025},
  doi     = {10.3390/app15020571},
}

@inproceedings{uwagbole2017inm,
  author    = {Uwagbole, Solomon Ogbomon and Buchanan, William J. and Fan, Lu},
  title     = {Applied Machine Learning Predictive Analytics to SQL Injection Attack Detection and Prevention},
  booktitle = {2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)},
  pages     = {1087--1090},
  year      = {2017},
  doi       = {10.23919/INM.2017.7987433},
  publisher = {IEEE}
}

@article{jemal2020ml,
  author  = {Jemal, Ines and Cheikhrouhou, Omar and Hamam, Habib and Mahfoudhi, Adel},
  title   = {SQL Injection Attack Detection and Prevention Techniques Using Machine Learning},
  journal = {International Journal of Applied Engineering Research},
  volume  = {15},
  number  = {6},
  pages   = {569--580},
  year    = {2020}
}

@article{muhammad2022sqli_ml,
  author  = {Muhammad, Taseer and Ghafory, Hamayoon},
  title   = {SQL Injection Attack Detection Using Machine Learning Algorithm},
  journal = {Mesopotamian Journal of CyberSecurity},
  volume  = {2022},
  pages   = {5--17},
  year    = {2022},
  doi     = {10.58496/MJCS/2022/002},
}

@article{chen2021sqli_dl,
  author  = {Chen, Ding and Yan, Qiseng and Wu, Chunwang and Zhao, Jun},
  title   = {SQL Injection Attack Detection and Prevention Techniques Using Deep Learning},
  journal = {Journal of Physics: Conference Series},
  volume  = {1757},
  number  = {1},
  pages   = {012055},
  year    = {2021},
  doi     = {10.1088/1742-6596/1757/1/012055},
}

@article{lu2023semantic,
  author  = {Lu, Dongzhe and Fei, Jinlong and Liu, Long},
  title   = {A Semantic Learning-Based SQL Injection Attack Detection Technology},
  journal = {Electronics},
  volume  = {12},
  number  = {6},
  pages   = {1344},
  year    = {2023},
  doi     = {10.3390/electronics12061344},
}

@article{crespo2023flowdata,
  author  = {Crespo Mart{\'\i}nez, Ignacio Samuel and Campazas Vega, Adri{\'a}n and Guerrero Higueras, {\'A}ngel Manuel and Riego Del Castillo, Virginia and Álvarez Aparicio, Claudia and Fern{\'a}ndez Llamas, Camino},
  title   = {SQL Injection Attack Detection in Network Flow Data},
  journal = {Computers \& Security},
  volume  = {127},
  pages   = {103093},
  year    = {2023},
  doi     = {10.1016/j.cose.2023.103093},
}

@inproceedings{marashdeh2021survey,
  author    = {Marashdeh, Zain and Suwais, Khaled and Alia, Mohammad},
  title     = {A Survey on SQL Injection Attack: Detection and Challenges},
  booktitle = {2021 International Conference on Information Technology (ICIT)},
  pages     = {957--962},
  year      = {2021},
  doi       = {10.1109/ICIT52682.2021.9491117},
  publisher = {IEEE}
}

@article{alghawazi2023rnnautoencoder,
  author  = {Alghawazi, Maha and Alghazzawi, Daniyal and Alarifi, Suaad},
  title   = {Deep Learning Architecture for Detecting SQL Injection Attacks Based on RNN Autoencoder Model},
  journal = {Mathematics},
  volume  = {11},
  number  = {15},
  pages   = {3286},
  year    = {2023},
  doi     = {10.3390/math11153286},
}

@article{thalji2023aenet,
  author  = {Thalji, Nisrean and Raza, Ali and Islam, Mohammad Shariful and Abdel Samee, Nagwan and Jamjoom, Mona M.},
  title   = {AE-Net: Novel Autoencoder-Based Deep Features for SQL Injection Attack Detection},
  journal = {IEEE Access},
  volume  = {11},
  pages   = {135507--135516},
  year    = {2023},
  doi     = {10.1109/ACCESS.2023.3337645},
}

@article{vadisetty2024intelligent,
  author  = {Vadisetty, Rahul and Chinta, Purna Chandra Rao and Moore, Chethan Sriharsha and Karaka, Laxmana Murthy and Sakuru, Manikanth and Bodepudi, Varun and Maka, Srinivasa Rao and Vangala, Srikanth Reddy},
  title   = {Intelligent Detection of Injection Attacks via SQL Based on Supervised Machine Learning Models for Enhancing Web Security},
  journal = {Journal of Artificial Intelligence and Big Data},
  volume  = {4},
  number  = {2},
  pages   = {109--119},
  year    = {2024},
  doi     = {10.31586/jaibd.2024.1333},
}

@article{ali2025hybrid,
  author  = {Ali, Sarbast H. and Mohammed, Arman I. and Mustafa, Sarwar MA. and Salih, Sardar Omar},
  title   = {Web Vulnerabilities Detection Using a Hybrid Model of CNN, GRU and Attention Mechanism},
  journal = {Science Journal of University of Zakho},
  volume  = {13},
  number  = {1},
  pages   = {58--64},
  year    = {2025},
  doi     = {10.25271/sjuoz.2024.12.3.1404},
}

@misc{rayten_sql_injection_dataset,
  author = {Rayten},
  title  = {SQL Injection Dataset},
  year   = {2021},
  url    = {https://www.kaggle.com/datasets/rayten/sql-injection-dataset},
  note   = {Kaggle dataset, accessed Nov.\ 2025}
}

@misc{Sajid_SQLInjectionDataset_2021,
  author = {Sajid576},
  title  = {SQL Injection Dataset},
  year   = {2021},
  url    = {https://www.kaggle.com/datasets/sajid576/sql-injection-dataset},
  note   = {Kaggle dataset, accessed Nov.\ 2025}
}

@article{kakisim2024,
  author  = {Kakisim, Arzu Gorgulu},
  title   = {A Deep Learning Approach Based on Multi-View Consensus for SQL Injection Detection},
  journal = {International Journal of Information Security},
  volume  = {23},
  number  = {2},
  pages   = {1541--1556},
  year    = {2024},
  doi     = {10.1007/s10207-023-00791-y},
}

@article{alazzawi2023,
  author  = {Alazzawi, Abdulbasit},
  title   = {SQL Injection Detection Using RNN Deep Learning Model},
  journal = {Journal of Applied Engineering and Technological Science},
  volume  = {5},
  number  = {1},
  pages   = {531--541},
  year    = {2023},
  doi     = {10.37385/jaets.v5i1.2864},
}

@article{alarfaj2023,
  author  = {Alarfaj, Fawaz Khaled and Khan, Nayeem Ahmad},
  title   = {Enhancing the Performance of SQL Injection Attack Detection through Probabilistic Neural Networks},
  journal = {Applied Sciences},
  volume  = {13},
  number  = {7},
  pages   = {4365},
  year    = {2023},
  doi     = {10.3390/app13074365},
}
