Computing Network Security Utilising AI

Abstract

Computer networks are indispensable in modern society, facilitating business operations, communication, and personal activities. However, the exponential growth of network connectivity has led to a surge in sophisticated cyber-attacks, posing significant threats to data security and organizational integrity. Traditional security measures, such as firewalls and intrusion detection systems (IDS), often fall short in addressing the complexity and frequency of these threats, necessitating advanced solutions. Artificial intelligence (AI) has emerged as a transformative technology in enhancing computer network security by enabling automated, intelligent systems capable of detecting, responding to, and preventing cyber threats in real-time. AI-based network security systems leverage technologies such as machine learning, neural networks, natural language processing (NLP), and data analytics to identify malicious activities, including zero-day exploits and targeted attacks, with greater accuracy and speed than human-dependent systems. These systems offer significant benefits, including improved threat detection accuracy, rapid response times, and adaptability to evolving threat landscapes. However, challenges such as false positives, limited training data, and adversarial attacks highlight the need for robust AI model development and comprehensive datasets. This research paper explores the architecture, benefits, and limitations of AI-based computer network security systems, emphasizing their potential to revolutionize cybersecurity. It also discusses current network security approaches, such as intrusion prevention systems (IPS) and secure sockets layer (SSL/TLS), and examines future developments, including the integration of deep learning and blockchain technology to enhance data privacy and threat detection. By addressing these challenges, AI-based systems can pave the way for more resilient and efficient network security frameworks, ensuring protection against the dynamic and ever-evolving cyber threat landscape.