Next-Gen Data Analytics and Intelligent Automation
The Evolution of Cybersecurity in the Age of Digital Transformation: How Businesses Can Stay Ahead of Emerging Threats in a Hyper-Connected World
Authors: Rajan Gupta, Supriya Madan, Kanta Malik and Priyanka Gupta
Publishing Date: 12-04-2026
ISBN: 978-81-975670-6-3
Abstract
In view of digital change, security has emerged as a critical challenge to enterprises that seek to guard their investments in a highly interconnected environment. This study examines how different algorithms identify cybersecurity threats, particularly Support Vector Machines (SVM), Decision Trees, Random Forests, and Neural Networks. To test the performance of these algorithms, we used a dataset of 10,000 cyber incidents. It was observed that Neural Networks scored the highest accuracy percentage of 94%, followed by Random Forests of 91%, SVM of 87 % and Decision Trees of 82%. The study also discusses the higher algorithms’ key value to accommodate complex and dynamic threats. For this reason, by comparing these findings with previous research, we highlight the importance of using sophisticated analyzes to improve threat identification and mitigations. Thus, the study emphasizes the necessity of applying digitalization initiatives with enhanced security to withstand new business risks. As a strategic guide, this paper delivers practical recommendations that can help companies adapt well to the complex environment of the social web.
Keywords
Cybersecurity, Digital Transformation, Neural Networks, Threat Detection, Algorithm Performance.
Cite as
Rajan Gupta, Supriya Madan, Kanta Malik and Priyanka Gupta, "The Evolution of Cybersecurity in the Age of Digital Transformation: How Businesses Can Stay Ahead of Emerging Threats in a Hyper-Connected World", In: Kusum Kumari Bharti and Noor Firdoos Jahan (eds), Next-Gen Data Analytics and Intelligent Automation, SCRS, India, 2026, pp. 75-85. https://doi.org/10.56155/978-81-975670-6-3-7