AI-Driven Network Security

Abstract

Protecting modern network security is becoming an increasingly complex task, especially given the evolution and growing sophistication of cyberattacks. Artificial intelligence (AI) presents an innovative approach that offers new possibilities to enhance the efficiency of security systems. This article explores the role of AI in network security systems, where it is employed as a primary tool for predicting and preventing cyber threats. Integrating AI into network security is essential, as traditional methods are often insufficient to address today’s more sophisticated and diverse cyberattack threats. AI’s ability to rapidly and effectively analyze large volumes of data enables systems to identify and respond to emerging challenges more swiftly than traditional systems often can.

The article reviews current research and literature detailing the advantages of AI, including its ability to provide rapid and effective responses, detect previously unknown threats, and reduce human intervention in automated systems. At the same time, it analyzes the challenges associated with integrating AI methods, such as high costs, the need for continual model updates and adaptation, and the complexity of AI systems. The article also provides practical examples showcasing AI’s successful application in the cybersecurity field. In conclusion, the article highlights the significant impact of AI methodologies on improving network security and emphasizes its future potential, while also noting the continuous need for innovation and addressing emerging challenges.