An Intelligent Approach for Classification In-Band SQLi Attacks Using Machine Learning Techniques

In-band SQL injection is the simplest type of SQL injection, and attackers use this type to modify the original query and get direct results from the modified query. Users get information from the database through the SQL injection code technique. The software market is increasing daily, and hackers' activities are also growing from 2019 to 2023, using the SQL injection approach to receive important user information. The researchers presented many models for the classification of SQL injection in the software market, but our proposed model will use updated dataset features in pre-processing and provide the required results. Further, our proposal will work on the Machine Learning algorithm bases. This research paper presents identification problems on websites and works on the top 10 vulnerabilities A07:2021. Our proposed model works on the classification of phishing emails using the ML Approach. Our proposed algorithms are KNN and Random Forest. It provides higher accuracy due to its feature extraction and classification process. The KNN algorithm accuracy was 95.9% and the logistic regression technique Random Forest was used to improve the 99.6% proposed model.