Artificial Intelligence in Cyber Defense: From Machine Learning Algorithms to Smart Network Security

The escalating sophistication and frequency of cyber threats demand advanced defense mechanisms that exceed traditional security paradigms. Artificial intelligence (AI), particularly through machine learning (ML) algorithms, has emerged as a pivotal force in transforming cyber defense systems. AI facilitates adaptive, proactive threat detection by enabling real-time identification and mitigation of sophisticated attacks, thereby strengthening network resilience. The integration of AI extends beyond mere detection to autonomous threat hunting, where AI-driven analytics work in synergy with conventional threat intelligence, offering comprehensive security solutions. This paradigm shift towards intelligent, automated defenses enables systems to respond dynamically to evolving threats with minimal human intervention. However, despite the promising advancements, challenges such as the interpretability of AI decisions and vulnerability to adversarial manipulations remain. Continued research is vital to addressing these concerns, ensuring that AI-driven systems can be trusted to enhance smart network security. The implementation of deep learning models, including recurrent neural networks (RNNs), plays a crucial role in processing large datasets and identifying subtle anomalies indicative of potential cyber threats. As AI continues to evolve, it becomes an indispensable element of modern cyber defense, offering innovative solutions to safeguard critical infrastructures against emerging threats.

کلیدواژه ها:

Artificial Intelligence ، Cyber Defense ، Machine Learning ، Smart Network Security ، Threat Detection