Ussatov, Nikita. Designing a vulnerability threat detection scanner with the use of machine learning models. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Designing a vulnerability threat detection scanner with the use of machine learning models
Organization :
Almaty University of Power Engineering and Telecommunications named after G. Daukeyev. Institute of Information and Computational Technologies
Abstract:
Vulnerabilities are a serious threat to operational systems, networks,
and applications. Identifying them in web services is crucial for
organizations aiming to safeguard their intellectual property and
data. This process involves automated scans to detect underlying
software issues that could lead to data corruption, loss, or system
compromise. Advanced technologies, including vulnerability
scanners based on automated testing tools, are employed to detect
attacks on web resources. This research focuses on developing an
effective vulnerability scanner and analyzing its functionality to
ensure information system security. Vulnerability scanners employ
various threat detection approaches, including signature detection,
behavioral analysis, heuristics, data flow analysis, and machine
learning models. Experiments in this work are devoted to the detection
of SQL injection threats. The steps, such as data preprocessing,
cleaning, normalization, feature extraction, and classification with
machine learning algorithms (Naïve Bayes, Logistic Regression,
Decision Tree, Random Forest, and XGBoost), were implemented to
train machine learning models. The trained models showed impressive
classification scores of 0.95 and above for Accuracy, Precision,
Recall, and F1-score metrics. These results prove the effectiveness
of utilizing a machine-learning approach for SQL injection identification
scanners
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2023
Modified:
2025-03-04
Issued:
2025-03-04
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BibliograpyCitation :
In King Mongkut's University of Technology Thonburi. The 13th International Conference on Advances in Information Technology (IAIT 2023) (Article 16). Bangkok : King Mongkut's University of Technology Thonburi