Suchergebnisse - Dataset SQL injection Anomaly detection

Application of Artificial Intelligence in Detecting SQL Injection Attacks von Augustine, Nwabudike, Md. Sultan, Abu Bakar, Osman, Mohd Hafeez, Sharif, Khaironi Yatim

“… Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored …”
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Feature Engineering for Injection Attack Detection: An Exploration from SQLI to XSS von Loginov, Alexander, Zincir-Heywood, Nur, Heywood, Malcolm

“… To this end, the proposed data preprocessing and feature engineering method is compared against state-of-the-art SQL injection detection on two different datasets using KNN, DT and SVM as classifiers …”
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Trident: Detecting SQL Injection Attacks via Abstract Syntax Tree-based Neural Network von Li, Yuanlin, Xu, Zhiwei, Zhou, Min, Wan, Hai, Zhao, Xibin

“… SQL injection attacks have posed a significant threat to web applications for decades …”
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Machine Learning and Deep Learning Techniques for Internet of Things Network Anomaly Detection—Current Research Trends von Rafique, Saida Hafsa, Abdallah, Amira, Musa, Nura Shifa, Murugan, Thangavel

“… AI-based anomaly detection systems are capable of identifying a wide range of threats in IoT environments, including brute force, buffer overflow, injection, replay attacks, DDoS assault, SQL …”
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SQL-GENIE: SQL Protection using GENerative Modeling for Anomaly Detection against Injection and Evolved Adversarial Attacks von Afrin, Sadia, Elsayed, Marwa A., Zincir-Heywood, Nur

“… The growing surge and sophistication of large-scale SQL injection (SQLi) attacks highlight the urgent need for advanced detection mechanisms to protect sensitive information, especially in cloud-based environments …”
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Detecting Web Attacks From HTTP Weblogs Using Variational LSTM Autoencoder Deviation Network von Jagat, Rikhi Ram, Sisodia, Dilip Singh, Singh, Pradeep

“… Recent studies focus on recognizing web attacks through deep neural network-based anomaly detection …”
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Advanced Detection and Prevention of SQL Injection Attacks Using Machine Learning Techniques for Enhanced Web Security von Pooja Panadiya, Prof. Manish Kumar Singhal

“… This paper presents an advanced framework for detecting and preventing SQL injection attacks using machine learning techniques to enhance web security …”
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A Multi-Class Intrusion Detection System Based on Continual Learning von Oikonomou, Chrysoula, Iliopoulos, Ilias, Ioannidis, Dimosthenis, Tzovaras, Dimitrios

“… ) based on continual learning with a CNN backbone. Using the LYCOS-IDS2017 dataset, the study explores several continuous learning techniques for identifying threats including denial-of-service and SQL injection …”
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Identification of Important Features at Different IoT layers for Dynamic Attack Detection von Haque, Safwana, El-Moussa, Fadi, Komninos, Nikos, Muttukrishnan, Rajarajan

“… One popular method of achieving this is with the use of intrusion detection systems (IDSs …”
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Enhancing SQL Query Security using Graph-based Hierarchical Embeddings with SMOTE and Advanced Neural Networks for Robust Detection von K, Mangaiyarkarasi, P. S., Uma Priyadarsini

“… SQL Injection Attacks (SQLIA) are still a significant security vulnerability, targeting issues in database query validation for intruder access …”
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A Thirty-Day Dataset of Malicious HTTP Requests Blocked by OWASP ModSecurity on a Production Web Server von Lucz, Geza, Forstner, Bertalan

“… ), resulting in its inclusion in the audit log due to suspected exploitation attempts. The dataset includes attack categories such as SQL injection, cross-site scripting (XSS …”
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Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment von Shahzadi, Shumaila, Ahmad, Fahad, Basharat, Asma, Alruwaili, Madallah, Alanazi, Saad, Humayun, Mamoona, Rizwan, Muhammad, Naseem, Shahid

“… With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time …”
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Intelligent Anomaly Detection in Database Security: A Triple-Loop Learning Framework von Kandolo, William

“… ), and meta-learning for real-time anomaly detection in SQL-based environments. To the best of our knowledge, TLL is the first framework to unify these three learning …”
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GENI: GANs Evaluation of iNjection attacks on IoT von Afrin, Sadia, Elsayed, Marwa A., Zincir-Heywood, Nur

“… In this research, we tackle the challenge of detecting SQL injection attacks and propose GENI, GANs evaluation of injection attacks on IoT networks …”
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Revolutionizing Threat Hunting in Communication Networks: Introducing a Cutting-Edge Large-Scale Multiclass Dataset von Al-Haija, Qasem Abu, Masoud, Zaid, Yasin, Assim, Alesawi, Karam, Alkarnawi, Yousef

“… In this paper, we develop a new threat-hunting model for communication networks and introduce a novel, cutting-edge, large-scale multiclass dataset to improve the security of network cognition …”
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Cyber Threat Attack Level Detection Using Machine Learning von R, Rahul, Mythili, S.

“… The study effectively proved the ability to detect numerous attack types, such as SQL injection …”
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LNKDSEA: Machine Learning Based IoT/IIoT Attack Detection Method von Koppula, Manasa, I, Leo Joseph L. M.

“… s. Practical defenses against this, including network anomaly detection, must be built to secure IoT networks …”
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Comprehensive Study of SQL Injection Attacks Mitigation Methods and Future Directions von Al-olaqi, Mohammed, Al-gailani, Ahmed, Rahman, M M Hafizur

“… Structured Query Language Injection Attack (SQLIA) as a form of cyber threats are among the most dangerous, easily penetrating the databases, and most web based applications …”
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Machine Learning Approach to Intrusion Detection: Performance Evaluation von Giraddi, Vishal, Giraddi, Shantala, D G, Narayan, Bidaragaddi, Anupama, Kanakareddi, Suvarna G

“… In this paper, authors aim to build framework based on various machine learning models (ML) to capture anomaly packets …”
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Identifying Security Threats in the System Using Automated Security Logs von Kanaparthi, Yadidiah, Abdellatif, Tamer Mohamed, Seyam, Ahmed Ali, Satrya, Gandeva Bayu

“… Several tests like failed login, unauthorized access, Denial of Service (DOS), and SQL Injection attempts were conducted to assess the security of the login page …”
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