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Related Experiment Video

Updated: Dec 25, 2025

Cross-Modal Multivariate Pattern Analysis

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

An Efficient Attribute-Based Access Control (ABAC) Policy Retrieval Method Based on Attribute and Value Levels in

Meiping Liu^1,2, Cheng Yang^1,2, Hao Li³

¹State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing 100024, China.

Sensors (Basel, Switzerland)

|April 5, 2020

Summary

This summary is machine-generated.

This study introduces an efficient method for Internet of Multimedia Things (IoMT) access control policy retrieval. The new approach significantly speeds up policy evaluation, improving multimedia service quality in the Internet of Things (IoT).

Keywords:

ABAC binary identifier depth index policy evaluation policy retrieval

Related Experiment Videos

Last Updated: Dec 25, 2025

Cross-Modal Multivariate Pattern Analysis

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

Area of Science:

Computer Science
Information Security
Multimedia Systems

Background:

The Internet of Multimedia Things (IoMT) offers intelligent services but faces significant multimedia data security and privacy challenges.
Attribute-Based Access Control (ABAC) provides fine-grained resource control in heterogeneous IoMT environments.
Inefficient access control policy evaluation in ABAC hinders multimedia service quality due to numerous users and policies.

Purpose of the Study:

To propose an efficient policy retrieval method for enhancing access control policy evaluation performance in multimedia networks.
To address the performance bottleneck in ABAC for IoMT environments.

Main Methods:

Developed a policy retrieval technique that first identifies relevant policies at the attribute level using binary identifiers.
Introduced a depth index to reconstruct the policy decision tree for improved efficiency at the attribute value level.

Main Results:

The proposed method demonstrated 3-5 times greater efficiency in access control policy evaluation compared to existing methods.
Simulation experiments confirmed the method's strong scalability under varying numbers and complexities of policies.

Conclusions:

The developed efficient policy retrieval method significantly improves the performance of access control in multimedia networks within the IoMT.
This advancement enhances the quality and scalability of multimedia application services in the Internet of Things (IoT).