Artificial Intelligence in Cybersecurity: Intelligent Threat Detection and Automated Defense Systems

Artificial Intelligence (AI) has emerged as a transformative technology in modern cybersecurity, enabling intelligent detection, prediction, and prevention of sophisticated cyber threats. With the rapid expansion of digital infrastructures, cloud computing, and Internet-connected devices, traditional rule-based security systems are increasingly inadequate in addressing dynamic and complex cyberattacks. AI-driven cybersecurity systems utilize machine learning, deep learning, and data analytics to analyze vast volumes of network traffic, identify anomalies, and detect malicious activities in real time. These intelligent systems can learn from historical attack patterns and adapt to emerging threats without requiring constant manual updates. Techniques such as anomaly detection, behavioral analysis, intrusion detection systems (IDS), and automated incident response mechanisms have significantly enhanced the effectiveness of modern cybersecurity frameworks. Furthermore, AI supports threat intelligence by correlating data from multiple sources and predicting potential vulnerabilities before exploitation occurs. Despite these advantages, AI-based cybersecurity solutions also face challenges including adversarial attacks, data privacy concerns, model interpretability, and the need for high-quality training data. This paper reviews the role of artificial intelligence in cybersecurity, discusses key analytical methods and tools, examines major real-world applications, and highlights current challenges and future research directions in building secure and intelligent digital infrastructures.

کلیدواژه ها:

Artificial Intelligence ، Cybersecurity ، Intrusion Detection Systems ، Machine Learning ، Threat Detection