AI-Powered Threat Detection in Cybersecurity Infrastructures
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I1P103Keywords:
Artificial Intelligence, Cybersecurity, Threat Detection, Machine Learning, Anomaly DetectionAbstract
Artificial Intelligence (AI) has emerged as a transformative force in cybersecurity, particularly in threat detection and response systems. By leveraging advanced algorithms and machine learning, AI enhances the ability to identify and mitigate cyber threats in real-time. This capability is crucial given the increasing complexity and frequency of cyberattacks targeting critical infrastructures. AI-driven systems analyze vast datasets from various sources, including network traffic, user behaviors, and historical incidents, to establish baselines of normal activity. When deviations from these patterns occur, AI can detect anomalies that may indicate potential threats, such as insider attacks or phishing attempts. Furthermore, AI automates the response process, significantly reducing the time required to address threats. This automation not only improves the speed and accuracy of threat detection but also alleviates the burden on human analysts by handling repetitive tasks. As AI continues to evolve, its applications in cybersecurity are expected to expand, offering enhanced predictive capabilities and adaptability to emerging threats. Overall, integrating AI into cybersecurity infrastructures represents a vital advancement in safeguarding digital assets against increasingly sophisticated cyber threats
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