Abstract
Sensitive data on e-commerce websites has been more vulnerable to cyberattacks in recent years, especially when those assaults take advantage of SQL injection flaws. Botnets are a ubiquitous hazard that increase the risks by automating large-scale attacks. This paper provides a new method for preventing SQL injection-based botnet assaults on e-commerce websites by creating and deploying an intrusion detection system (IDS) based on honeypots. By tricking attackers into interacting with dummy systems and then watching and analyzing their actions, the suggested solution seeks to proactively detect and neutralize such attacks. Our system improves the security posture of e-commerce platforms by using a combination of machine learning algorithms, anomaly detection techniques, and honeypot deployment. This protects sensitive client data and maintains business integrity. Keywords: E-commerce, SQL injection, Botnet, Honeypot, Intrusion Detection System, Machine Learning, Anomaly Detection
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