Academic literature on the topic 'SQL injection attack detection'

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Journal articles on the topic "SQL injection attack detection"

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Mr., Vishal Andodariya. "SQL Injection Attack Detection and Prevention Techniques to Secure Web Site." International Journal of Trend in Scientific Research and Development 2, no. 4 (2019): 624–28. https://doi.org/10.31142/ijtsrd13034.

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Structured Query Language SQL Injection is a code injection technique that exploits security vulnerability occurring in database layer of web applications 8 . According to Open Web Application Security Projects OWASP , SQL Injection is one of top 10 web based attacks 10 . This paper shows the basics of SQL Injection attack, types of SQL Injection Attack according to their classification. It also describes the survey of different SQL Injection attack detection and prevention. At the end of this paper, the comparison of different SQL Injection Attack detection and prevention is shown. Mr. Vishal
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Silva, Rui Filipe, Raul Barbosa, and Jorge Bernardino. "Intrusion Detection Systems for Mitigating SQL Injection Attacks." International Journal of Information Security and Privacy 14, no. 2 (2020): 20–40. http://dx.doi.org/10.4018/ijisp.2020040102.

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Databases are widely used by organizations to store business-critical information, which makes them one of the most attractive targets for security attacks. SQL Injection is the most common attack to webpages with dynamic content. To mitigate it, organizations use Intrusion Detection Systems (IDS) as part of the security infrastructure, to detect this type of attack. However, the authors observe a gap between the comprehensive state-of-the-art in detecting SQL Injection attacks and the state-of-practice regarding existing tools capable of detecting such attacks. The majority of IDS implementat
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Senouci, Oussama, and Nadjib Benaouda. "Advanced deep learning framework for detecting SQL injection attacks based on GRU Model." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 2 (2024): e11299. https://doi.org/10.54021/seesv5n2-596.

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SQL injection attacks are a major danger to data security in application systems, leveraging weaknesses to illicitly access and change sensitive data. Traditional detection methods, such rule-based systems and supervised machine learning, struggle to adapt to new SQL injection attack strategies. This study presents an Enhanced Deep Learning Framework for SQL Injection Detection utilizing the Gated Recurrent Unit (GRU) model to overcome constraints. To discover new attack patterns, the proposed framework uses a dynamic learning process instead of static detection methods. By examining SQL query
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Alghawazi, Maha, Daniyal Alghazzawi, and Suaad Alarifi. "Detection of SQL Injection Attack Using Machine Learning Techniques: A Systematic Literature Review." Journal of Cybersecurity and Privacy 2, no. 4 (2022): 764–77. http://dx.doi.org/10.3390/jcp2040039.

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An SQL injection attack, usually occur when the attacker(s) modify, delete, read, and copy data from database servers and are among the most damaging of web application attacks. A successful SQL injection attack can affect all aspects of security, including confidentiality, integrity, and data availability. SQL (structured query language) is used to represent queries to database management systems. Detection and deterrence of SQL injection attacks, for which techniques from different areas can be applied to improve the detect ability of the attack, is not a new area of research but it is still
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Hafriadi, Fajar Dzulnufrie, and Rizka Ardiansyah. "NETWORK'S ACCESS LOG CLASSIFICATION FOR DETECTING SQL INJECTION ATTACKS WITH THE LSTM ALGORITHM." Jurnal Teknik Informatika (Jutif) 5, no. 4 (2024): 745–52. https://doi.org/10.52436/1.jutif.2024.5.4.2157.

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SQL Injection attacks are one of the popular web attacks. This attack is a network security problem focused on the application layer which is one of the causes of a large number of user data leaks. Currently available SQL detection techniques mostly rely on manually created features. Generally, the detection results of SQL Injection attacks depend on the accuracy of feature extraction, so they cannot overcome increasingly complex SQL Injection attacks on various systems. Responding to these problems, this research proposes a SQL Injection attack detection method using the long short term memor
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Abebe, Anduamlak, Yonas Belay, Adane Belay, and Seffi Gebeyehu. "SQL INJECTION ATTACKS DETECTION: A PERFORMANCE COMPARISON ON MULTIPLE CLASSIFICATION MODELS." Ethiopian International Journal of Engineering and Technology 2, no. 1 (2024): 22–38. http://dx.doi.org/10.59122/154cfc15.

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SQL injection attacks are a common and serious security threat to web applications, where malicious users exploit vulnerabilities to gain unauthorized access to sensitive data or manipulate the database. Detecting and preventing SQL injection attacks is crucial for ensuring the security and integrity of web applications. While there have been studies on using machine learning for detecting SQL injection attacks, there is a lack of comprehensive comparative analysis that evaluates the performance of multiple classification models specifically for this purpose. Existing research often focuses on
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Dalai, Asish Kumar, and Sanjay Kumar Jena. "Neutralizing SQL Injection Attack Using Server Side Code Modification in Web Applications." Security and Communication Networks 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/3825373.

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Reports on web application security risks show that SQL injection is the top most vulnerability. The journey of static to dynamic web pages leads to the use of database in web applications. Due to the lack of secure coding techniques, SQL injection vulnerability prevails in a large set of web applications. A successful SQL injection attack imposes a serious threat to the database, web application, and the entire web server. In this article, the authors have proposed a novel method for prevention of SQL injection attack. The classification of SQL injection attacks has been done based on the met
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Siddiqa, Ayesha. "Web Based Intrusion Detection System for SQLIA." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 11 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26708.

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SQL Injection Attack (SQLIA) refers to an injection attack wherein an attacker can execute malicious SQL statements that control a web application’s database server. By leveraging SQL Injection vulnerability, given the right circumstances, an attacker can use it to bypass a web application’s authentication and authorization mechanisms and retrieve the contents of an entire database. SQL Injection can also be used to add, modify and delete records in a database, affecting data integrity. The main idea of our work is to allow developers the freedom to write and execute code without having to wor
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Abdulmalik, Yazeed. "An Improved SQL Injection Attack Detection Model Using Machine Learning Techniques." International Journal of Innovative Computing 11, no. 1 (2021): 53–57. http://dx.doi.org/10.11113/ijic.v11n1.300.

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SQL Injection Attack (SQLIA) is a common cyberattack that target web application database. With the ever increasing and varying techniques to exploit web application SQLIA vulnerabilities, there is no a comprehensive method that can solve this kind of attacks. Therefore, these various of attack techniques required to establish many methods against in order to mitigate its threats. However, most of these methods have not yet been evaluated, where it is still just theories and require to implement and measure its performance and set its limitation. Moreover, most of the existing SQL injection co
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Kumar, Ashish, and Sumitra Binu. "Proposed Method for SQL Injection Detection and its Prevention." International Journal of Engineering & Technology 7, no. 2.6 (2018): 213. http://dx.doi.org/10.14419/ijet.v7i2.6.10569.

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SQL injection attack is a commonly used method to attack the database server. Injection attacks enable the attacker to bypass the validation and authorization mechanisms used by database server and gain access to the database. The easiest way to launch this attack is by exploiting the loopholes in the validation of user inputs provided through login pages. Each login page that a user visits can contribute towards revealing the identity of the user. Feedbacks given by the server while executing an SQL code can reveal information regarding the vulnerabilities in the validation process of the dat
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Dissertations / Theses on the topic "SQL injection attack detection"

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Bahureková, Beáta. "Technika SQL injection - její metody a způsoby ochrany." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2020. http://www.nusl.cz/ntk/nusl-433304.

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SQL injection is a technique directed against web applications using an SQL database, which can pose a huge security risk. It involves inserting code into an SQL database, and this attack exploits vulnerabilities in the database or application layer. The main goal of my thesis is to get acquainted with the essence of SQL injection, to understand the various methods of this attack technique and to show ways to defend against it. The work can be divided into these main parts, which I will discuss as follows.In the introductory part of the work I mention the theoretical basis concerning SQL injec
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Whitelaw, Clayton. "Precise Detection of Injection Attacks on Concrete Systems." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/6051.

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Injection attacks, including SQL injection, cross-site scripting, and operating system command injection, rank the top two entries in the MITRE Common Vulnerability Enumeration (CVE) [1]. Under this attack model, an application (e.g., a web application) uses some untrusted input to produce an output program (e.g., a SQL query). Applications may be vulnerable to injection attacks because the untrusted input may alter the output program in malicious ways. Recent work has established a rigorous definition of injection attacks. Injections are benign iff they obey the NIE property, which states tha
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Pandey, Amit Kumar. "Securing Web Applications From Application-Level Attack." Kent State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=kent1181098075.

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Uwagbole, Solomon. "A pattern-driven corpus to predictive analytics in mitigating SQL injection attack." Thesis, Edinburgh Napier University, 2018. http://researchrepository.napier.ac.uk/Output/1538260.

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The back-end database provides accessible and structured storage for each web application's big data internet web traffic exchanges stemming from cloud-hosted web applications to the Internet of Things (IoT) smart devices in emerging computing. Structured Query Language Injection Attack (SQLIA) remains an intruder's exploit of choice to steal confidential information from the database of vulnerable front-end web applications with potentially damaging security ramifications. Existing solutions to SQLIA still follows the on-premise web applications server hosting concept which were primarily dev
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Sjöström, Linus. "Detecting SQL Injection Attacks in VoIP using Real-time Deep Packet Inspection : Can a Deep Packet Inspection Firewall Detect SQL Injection Attacks on SIP Traffic with Reasonable Performance?" Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161072.

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The use of the Internet has increased over the years, and it is now an integral part of our daily activities, as we often use it for everything from interacting on social media to watching videos online. Phone calls nowadays tend to use Voice over IP (VoIP), rather than the traditional phone networks. As with any other services using the Internet, these calls are vulnerable to attacks. This thesis focus on one particular attack: SQL injection in the Session Initial Protocol (SIP), where SIP is a popular protocol used within VoIP. To find different types of SQL injection, two classifiers are im
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Gopali, Gopali. "Protecting Web Applications from SQL Injection Attacks- Guidelines for Programmers Master Thesis." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20238.

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Injektionsattack är den mest kritiska säkerhetsapplikationen för webbapplikationer, och SQL-injektion (SQLi) -attack är den mest rapporterade injektionsattacken på webbapplikationer. I denna avhandling har vi identifierat angreppsteknikerna som används av angripare och vi ger också riktlinjer så att programmerarna kan skriva webbapplikationskoder på ett säkert sätt för att förhindra SQLi-attackerna.Metoden som tillämpas för forskningen är litteraturstudie och vi använde vägen bevis genom demonstration för att få den tydliga bilden. Det första steget var att ta reda på kodningsfelen, då utforma
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Deshpande, Chinmay Ravindra. "Hardware Fault Attack Detection Methods for Secure Embedded Systems." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/82141.

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In our daily life, we are increasingly putting our trust in embedded software applications, which run on a range of processor-based embedded systems from smartcards to pay-TV units. This trend expands the threat model of embedded applications from software into hardware. Over the last 20 years, fault attacks have emerged as an important class of hardware attacks against embedded software security. In fault attacks, an adversary breaks the security by injecting well chosen, targeted faults during the execution of embedded software, and systematically analyzing softwares fault response. In thi
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Nsambu, Emmanuel, and Danish Aziz. "The Defense Against the latest Cyber Espionage both insider and outsider attacks." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-16477.

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This study was carried out with the intention of examining the defensive mechanism employed against the latest cyber espionage methods including both insider and outsider attacks. The main focus of this study was on web servers as the targets of the cyber attacks. Information in connection to the study was obtained from researchers’ online articles. A survey was also conducted at MidSweden University in order to obtain information about the latest cyber attacks on web servers and about the existing defensive mechanism against such attacks. The existing defensive mechanism was surveyed and a si
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Andersson, Stig. "Detecting and characterising malicious executable payloads." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/30325/1/Stig_Andersson_Thesis.pdf.

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Buffer overflow vulnerabilities continue to prevail and the sophistication of attacks targeting these vulnerabilities is continuously increasing. As a successful attack of this type has the potential to completely compromise the integrity of the targeted host, early detection is vital. This thesis examines generic approaches for detecting executable payload attacks, without prior knowledge of the implementation of the attack, in such a way that new and previously unseen attacks are detectable. Executable payloads are analysed in detail for attacks targeting the Linux and Windows operating syst
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Andersson, Stig. "Detecting and characterising malicious executable payloads." Queensland University of Technology, 2009. http://eprints.qut.edu.au/30325/.

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Buffer overflow vulnerabilities continue to prevail and the sophistication of attacks targeting these vulnerabilities is continuously increasing. As a successful attack of this type has the potential to completely compromise the integrity of the targeted host, early detection is vital. This thesis examines generic approaches for detecting executable payload attacks, without prior knowledge of the implementation of the attack, in such a way that new and previously unseen attacks are detectable. Executable payloads are analysed in detail for attacks targeting the Linux and Windows operating syst
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Book chapters on the topic "SQL injection attack detection"

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Shahriar, Hossain, Sarah North, and Wei-Chuen Chen. "Client-Side Detection of SQL Injection Attack." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-642-38490-5_46.

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Pan, Zhang, Qianli Huang, Ziqing Tian, et al. "Deep Learning Based SQL Injection Attack Detection." In Communications in Computer and Information Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1277-9_10.

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Hubskyi, Oleksandr, Tetiana Babenko, Larysa Myrutenko, and Oleksandr Oksiiuk. "Detection of SQL Injection Attack Using Neural Networks." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58124-4_27.

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Alkhalaf, Abeer, Bassel Alkhatib, and Safwan Ghanem. "SQL Injection Attack Detection Using Machine Learning Techniques." In Proceedings of the 7th International Conference on Advance Computing and Intelligent Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-5015-7_13.

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Lin, HongQing, JianQi Shao, Ting Sun, Xue Zou, and HaiFeng Wang. "SQL Injection Attack Detection Based on Error Code Knowledge." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2757-5_50.

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Choraś, Michał, and Rafał Kozik. "Evaluation of Various Techniques for SQL Injection Attack Detection." In Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00969-8_74.

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Choraś, Michał, Rafał Kozik, Damian Puchalski, and Witold Hołubowicz. "Correlation Approach for SQL Injection Attacks Detection." In Advances in Intelligent Systems and Computing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33018-6_18.

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Mahesh, R., Samuel Chellathurai, Meyyappan Thirunavukkarasu, and Pandiselvam Raman. "SQL Injection Attack Detection and Prevention Based on Manipulating the SQL Query Input Attributes." In Computational Sciences and Sustainable Technologies. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-50993-3_17.

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Sirmulla, AsifIqbal, and M. Prabhakar. "Stacked Autoencoder-Based Deep Unsupervised Learning Approach for SQL Injection Attack Detection." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-7592-7_4.

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Wu, Tsu-Yang, Jeng-Shyang Pan, Chien-Ming Chen, and Chun-Wei Lin. "Towards SQL Injection Attacks Detection Mechanism Using Parse Tree." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12286-1_38.

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Conference papers on the topic "SQL injection attack detection"

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S, Tamilselvan, and K. France. "SQL Injection Attack Detection in Web Applications Using Machine Learning Algorithms." In 2025 8th International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2025. https://doi.org/10.1109/icoei65986.2025.11013708.

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Zhang, Yingying, Zhengdan Jiang, Xingkai Cheng, Han Wu, Zonghang Tian, and Shuting Lou. "A Method of SQL Injection Attack Detection Based on Large Language Models." In 2024 2nd International Conference on Computer Network Technology and Electronic and Information Engineering (CNTEIE). IEEE, 2024. https://doi.org/10.1109/cnteie66268.2024.00035.

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Shakya, RDN, D. N. S. Dharmaratne, and Manjula Sandirigama. "Detection of SQL Injection Attacks Using Machine Learning Techniques." In 2024 International Conference on Electrical, Communication and Computer Engineering (ICECCE). IEEE, 2024. https://doi.org/10.1109/icecce63537.2024.10823462.

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Guan, Yinfan, Wenrui Zhou, Huiling Wang, and Ling Lin. "Feature Fusion-Based Detection of SQL Injection and XSS Attacks." In 2024 5th International Conference on Information Science, Parallel and Distributed Systems (ISPDS). IEEE, 2024. http://dx.doi.org/10.1109/ispds62779.2024.10667632.

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Lamba, Harsimran Kaur, Heet Gala, Rejo Mathew, and Sanjana Shinde. "AI Based Intrusion Detection for DDoS and SQL Injection Attacks." In 2024 First International Conference for Women in Computing (InCoWoCo). IEEE, 2024. https://doi.org/10.1109/incowoco64194.2024.10863756.

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Li, Qinghao, Zhida Guo, Xiaoli Li, Ling Zhao, Haobin Shen, and Yunsi Jiang. "Research on Threat Detection of SQL Injection Attacks in Large Scale Web Applications." In 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering (ACTCE). IEEE, 2024. https://doi.org/10.1109/actce65085.2024.00046.

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Altunay, Hakan Can. "Detection of SQL Injection Attacks Using Machine Learning Algorithms Based on NLP-Based Feature Extraction." In 2024 9th International Conference on Computer Science and Engineering (UBMK). IEEE, 2024. https://doi.org/10.1109/ubmk63289.2024.10773483.

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Yegnidemir, Emir, and Rahamatullah Khondoker. "SPSDN: A Security Platform for SDN Networks with an AI-based SQL Injection Attack Detection and Mitigation as An Example Service." In 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN). IEEE, 2024. http://dx.doi.org/10.1109/icmlcn59089.2024.10624751.

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Zaidan, Mustaghfir Naufal, Parman Sukarno, and Aulia Arif Wardana. "Collaborative Detection of SQL Injection Attacks using SIEM, Multi-Wazuh Agents, and Diverse Web Application Firewalls." In 2024 5th International Conference on Communications, Information, Electronic and Energy Systems (CIEES). IEEE, 2024. https://doi.org/10.1109/ciees62939.2024.10811420.

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Imran, Hafiz Muhammad Sajid, Kainat Abdullah, Muhammad Asif Habib, and Mudassar Ahmad. "Enhanced Detection and Prevention of SQL Injection and Cross-Site Scripting Attacks in Web Applications: Analysing Algorithms and Threat Modeling Approaches." In 2024 18th International Conference on Open Source Systems and Technologies (ICOSST). IEEE, 2024. https://doi.org/10.1109/icosst64562.2024.10871142.

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Reports on the topic "SQL injection attack detection"

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Bri Rolston. Attack methodology Analysis: SQL Injection Attacks and Their Applicability to Control Systems. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/911631.

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