Ensemble learning techniques against structured query language . . . This study introduced DSQLIA, employing ensemble learning algorithms-Bagging, Stacking, and AdaBoost classifiers-for SQL injection detection this research underscores the potential of ensemble learning in fortifying web application security against SQL injection attacks, emphasizing the AdaBoost classifier's exceptional performance in
SQL Injection Detection using Machine Learning: A Review SQL injection attacks are critical security vulnerability exploitation in web applications, posing risks to data, if successfully executed, allowing attackers to gain unauthorised access to sensitive data Due to the absence of a standardised structure, traditional signature-based detection methods face challenges in effectively detecting SQL injection attacks
SQL Injection Detection using Machine Learning: A Review - Semantic Scholar MJoSHT Vol 10, No 1 (2024) 39 [mjosht usim edu my] Article SQL Injection Detection using Machine Learning: A Review Mohammed A M Oudah and Mohd Fadzli Marhusin Cyber Security and Systems (CSS) Research Unit, Faculty of Sciences and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
AN ENHANCED SQL INJECTION DETECTION USING ENSEMBLE METHOD SQL injection is a cybercrime that attacks websites This issue is still a challenging issue in the realm of security that must be resolved These attacks are very costly financially, which count millions of dollars each year Due to large data leaks, the losses also impact the world economy, which averages nearly $50 per year, and most of them are caused by SQL injection
Enhancing SQL Injection Detection Using Ensemble Learning and Boosting . . . This paper presents a comparative study of various decision models for detecting SQL injection attacks SQL injection remains one of the most pervasive and critical security threats to web applications, allowing attackers to gain unauthorized access to databases and manipulate data Traditional detection methods often fall short due to the evolving nature of attack techniques and the
Ensemble learning techniques against structured query language . . . Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Electrical Engineering and Computer Science, Jun 2024 necessitating robust detection measures This study introduced DSQLIA, employing ensemble learning algorithms-Bagging, Stacking, and AdaBoost classifiers-for SQL injection detection
D6a02f587e1925471013 c41755792933 afef - Indonesian Journal of . . . Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9 , No 3 , September 2021 , pp 702 ~ 718 SQL injection (SQLi), a well-known exploitation technique, is a serious risk International Conference on Electrical Engineering and Computer Science (ICECOS), 2017 [25] M Chenyu and G Fan, “Defending SQL injection
Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Electrical Engineering and Computer Science (IJEECS), p-ISSN: 2502-4752, e-ISSN: 2502-4760, is a monthly peer-reviewed international journal in English The IJEECS is published by the Institute of Advanced Engineering and Science (IAES) The purpose of this journal is to disseminate high-quality articles that are devoted to discussing any and all elements of the most
Ensemble Machine Learning Approaches for Detection of SQL Injection Attack In in-band SQL injection attack, the attacker extracts the information from the same channel that is used for send ing the query or performing the attack In out- of-band SQL injection attack, the attacker extracts the information with the help of another channel like email In inferential SQL injection attack, the attacker does not extract the
Enhancing SQL Injection Attack Prevention: A Framework for Detection . . . SQL injection attacks (SQLIAs) pose increasing threats as more organizations adopt vulnerable web applications and databases By manipulating queries, SQLIAs access and destroy confidential data This paper delivers three contributions around improving SQLIA detection research: first, a literature review assessing current detection prevention systems to produce an SQL injection detection