A New Approach to Data Analysis Using Machine Learning for Cybersecurity

Abstract

The internet has become an indispensable tool for organizations, permeating every facet of their operations. Virtually all companies leverage Internet services for diverse purposes, including the digital storage of data in databases and cloud platforms. Furthermore, the rising demand for software and applications has led to a widespread shift toward computer-based activities within the corporate landscape. However, this digital transformation has exposed the information technology (IT) infrastructures of these organizations to a heightened risk of cyber-attacks, endangering sensitive data. Consequently, organizations must identify and address vulnerabilities within their systems, with a primary focus on scrutinizing customer-facing websites and applications. This work aims to tackle this pressing issue by employing data analysis tools, such as Power BI, to assess vulnerabilities within a client’s application or website. Through a rigorous analysis of data, valuable insights and information will be provided, which are necessary to formulate effective remedial measures against potential attacks. Ultimately, the central goal of this research is to demonstrate that clients can establish a secure environment, shielding their digital assets from potential attackers.