Strengthening E-Commerce Security Through Innovative IT Project Management: Harnessing the CatBoost Algorithm for Proactive Vulnerability Attack Mitigation

Abstract

These attacks target weaknesses in e-commerce websites, apps, databases, and systems to obtain access without authorization, steal sensitive data, interrupt services, or engage in fraud, which poses additional difficulties. To overcome these issues, we proposed machine learning (ML) based techniques in IT project management for the e-commerce industry, it has several advantages that improve project productivity, decision-making, and success.For assessing the security of web-based applications, Burp Suite is a strong and popular cyber security tool. To find and fix vulnerabilities in internet-based applications, security experts, malicious hackers, and testers of vulnerability frequently utilize it. It offers an extensive number of features to find weaknesses.This research proposes anovelapproach utilizing the Burp Suite and CatBoost gradient boosting machine learning algorithm to detect and forecast issues in E-commerce IT project management systems, specifically focusing on mitigating vulnerabilities and attacks. Furthermore, if an attack node is detected by DBN, the control is transferred to a lightweight lure approach that consistently mitigates the most frequent attack nodes not disrupting normal connections. A prospective avenue for improving the management of IT projects is provided by the utilization of machine learning.