Cyber Security for Machine Learning Systems in Business Data
K P Vidyashree, T.J. Shivani, K S Shilpa, Vinayakumar Ravi · 2025
Today, in the wake of digitization and the Internet of Things, a mass of cybersecurity data is emerging. Effective management of cyber problems and attacks is increasingly necessary for global cybersecurity. Conventional security methods are lacking in dealing with the rapid transformation of various cyber threats. In dealing with the current challenges of security, artificial intelligence, more specifically machine learning, plays an important role in analyzing security data. It nurtures a security system that is flexible, automated, and current. This chapter covers a detailed examination of the capabilities of machine learning algorithms to extract significant insights from cybersecurity data for enhancing intelligent data analysis and automation systems. We present several pragmatic implementations that include the enhancement of proactive cyber defense by leveraging automation, data-driven intelligence, and smart decision-making processes over conventional techniques. We conclude the analysis with a broad view of applications of machine learning in the security realm as well as other key areas of research. Finally, we would like to briefly discuss the current state of machine learning and how that will drive the advancement of cyber security further into the future.