Scholarlink

In today’s digital world, protecting sensitive data is crucial for organizations. Traditional access control systems, which rely on fixed roles and attributes, often fail to adapt to evolving security threats. Behavior-Based Access Control (BBAC) addresses the shortcomings of conventional methods by dynamically adjusting user permissions in real time based on observed actions. To enhance BBAC, Large Language Models (LLMs) are incorporated, leveraging advanced language processing to interpret access policies, analyzing behavior patterns, and making context-aware decisions. Integrating Large Language Models (LLMs) enables the system to detect suspicious activities, such as unauthorized actions or policy violations, with greater accuracy. Consequently, BBAC systems achieve flexible and intelligent access control, balancing security with workflow efficiency. Early experiments using synthetic data confirm the model’s effectiveness. The experimental results demonstrate that the model is efficient, accurate, and shows potential in detecting abnormal behaviors among authorized users.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Access Control Method Against Unauthorized and Noncompliant Behaviors Leveraging Large Language Models

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Nastaran Farhadighalati,
  • Sepideh Kalateh,
  • Luis A. Estrada-Jimenez,
  • Sanaz Nikghadam-Hojjati,
  • José Barata

摘要

In today’s digital world, protecting sensitive data is crucial for organizations. Traditional access control systems, which rely on fixed roles and attributes, often fail to adapt to evolving security threats. Behavior-Based Access Control (BBAC) addresses the shortcomings of conventional methods by dynamically adjusting user permissions in real time based on observed actions. To enhance BBAC, Large Language Models (LLMs) are incorporated, leveraging advanced language processing to interpret access policies, analyzing behavior patterns, and making context-aware decisions. Integrating Large Language Models (LLMs) enables the system to detect suspicious activities, such as unauthorized actions or policy violations, with greater accuracy. Consequently, BBAC systems achieve flexible and intelligent access control, balancing security with workflow efficiency. Early experiments using synthetic data confirm the model’s effectiveness. The experimental results demonstrate that the model is efficient, accurate, and shows potential in detecting abnormal behaviors among authorized users.