Linear Time Algorithms to Restrict Insider Access using Multi-Policy Access Control Systems

Area of Science:

• Computer Science
• Cybersecurity
• Information Security

Background:

• Access control mechanisms aim to limit information access but individual methods are often inadequate.
• Ensemble approaches enhance security but face scalability challenges due to complex calculations.
• Next Generation Access Control (NGAC) by ANSI is a promising but historically unscalable approach.

Purpose of the Study:

• To demonstrate the scalability of the Next Generation Access Control (NGAC) approach.
• To address the performance limitations of existing NGAC implementations.
• To provide an efficient method for access control and user privilege review.

Main Methods:

• Reformulated the set-theoretic NGAC standard into a graph-theoretic approach.
• Applied standard graph algorithms to achieve linear time complexity for access control decisions.
• Developed a novel, linear time visualization mechanism for user access rights.

Main Results:

• Achieved linear time complexity for access control decision-making, significantly improving upon previous cubic algorithms.
• Demonstrated efficient querying of user file accessibility and file access permissions.
• Introduced a scalable visualization tool for reviewing access rights across ensemble access control policies.

Conclusions:

• The graph-theoretic reformulation makes NGAC efficient and scalable.
• The developed methods enable practical implementation of ensemble access control strategies.
• This work facilitates the use of NGAC for mitigating insider threats through improved access control and visualization.