Multi Class SQLI

Mendeley Data 2026 Dataset Open access

Read full text
Authors: Ahmed Ibrahim, Hasanen Alyasiri
DOI: 10.17632/6n67ymrwy8
Cited by: 0

Abstract

This dataset comprises over 38,000 records representing multiple classes of SQL Injection (SQLi) attacks, specifically designed for research and development of Intrusion Detection Systems (IDS). The dataset includes more than five distinct attack types, with each record capturing features that describe the behavior of malicious web requests.

Fields of Study & Subjects

Web Application Security Vulnerabilities Network Security and Intrusion Detection Adversarial Robustness in Machine Learning

Publication details

Journal / source
Mendeley Data
Publication date
14 January 2026
Document type
Dataset