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Opportunities and Challenges in Applying Machine Learning for Access Control
  • Sora Nakamura,
  • Yuto Tanaka
Sora Nakamura

Corresponding Author:[email protected]

Author Profile
Yuto Tanaka

Abstract

Access control systems are important in regulating who can access physical facilities , computer systems, and data resources. However, traditional access control systems have limitations in adapting to changing user behavior and evolving security threats. We argue that applying machine learning is a promising direction to access control systems can enhance their accuracy, efficiency, and effectiveness. Machine learning can help identify and mitigate security risks in real-time by detecting patterns of suspicious activity that may indicate a security breach or attempted attack. It can also learn to identify anomalies and raise alerts, enabling security personnel to respond quickly and prevent potential security incidents.