Comparative Analysis of Traditional vs. AI-Driven Network Security
Nobhonil Roy Choudhury, Shyamalendu Paul, Sanchita Ghosh · Advances in wireless technologies and telecommunication book series · 2024
The increasing complexity of cyber threats has exposed the limitations of traditional network security methods like firewalls and IDS, which rely on established guidelines and signature-based detection. AI introduces a new paradigm, leveraging machine learning, behavioral analytics, and automated threat detection to enhance efficiency, accuracy, and response time. AI-driven systems handle large data volumes better, reduce false positives, and adapt to new threats, making them more effective against zero-day attacks. While initial costs are high, AI's long-term benefits include scalability, adaptability, and cost-efficiency. Ethical concerns and complexity remain challenges, but integrating AI with traditional methods can create a more resilient security posture.