[Paper Review] Application of Intelligent Multi Agent Based Systems For E-Healthcare Security

Z. Faizal Khan, Omar Reyad|arXiv (Cornell University)|Apr 2, 2020

Innovation in Digital Healthcare Systems4 citations

TL;DR

This paper proposes an Intelligent-Based Access Control (IBAC) model using multi-agent systems to enhance security and privacy in electronic healthcare records (EHR). The system employs specialized intelligent agents—user interface, authentication, connection establishment, and management agents—to enforce role-based access control, ensuring secure, real-time, and patient-controlled data sharing while mitigating threats across data collection, transmission, and storage levels.

ABSTRACT

In recent years, availability and usage of extensive systems for Electronic Healthcare Record (EHR) is increased. In medical centers such hospitals and other laboratories, more health data sets were formed during the treatment process. In order to enhance the standard of the services provided in healthcare, these records where shared and can be used by various users depends on their requirements. As a result, notable issues in the security and privacy where obtained which should be monitored and removed in order to make the use of EHR more effectively. Various researches have been done in the past literature for improving the standards of the security and privacy in E-health systems. In spite of this, it is not completely enhanced. In this paper, a comprehensive analysis is done by selecting the existing approaches and models which were proposed for the security and privacy of the E-healthcare systems. Also, a novel Intelligent-based Access Control Security Model (IBAC) based on multi agents is proposed to maintain and support the security and privacy of E-healthcare systems. This system uses agents in order to maintain security and privacy while accessing the E-health data between the users.

Motivation & Objective

• Address growing security and privacy threats in electronic healthcare records (EHR) due to increasing data sharing across medical institutions.
• Identify critical vulnerabilities in EHR systems at data collection, transmission, and storage levels.
• Develop a novel, patient-centric access control model that enhances trust and data confidentiality in E-health systems.
• Overcome limitations of existing security models by integrating intelligent agents for dynamic, role-based access control.
• Provide a scalable and efficient framework for securing EHR systems using autonomous, specialized agents.

Proposed method

• Design a multi-agent architecture with four specialized intelligent agents: user interface, authentication, connection establishment, and connection management.
• Implement role-based access control (RBAC) through the authentication agent, validating user credentials and permissions before granting access.
• Use a connection establishment agent to securely initiate and maintain communication channels between users and EHR systems.
• Store connection and authentication policies in a centralized database for auditability and dynamic policy enforcement.
• Apply a decision logic algorithm: if user credentials (UN) match the access policy (AP), establish connection; otherwise, deny access.
• Integrate patient data fields (e.g., age, blood group, vital signs, medical history) and user credentials into a secure, structured database for access control.

Experimental results

Research questions

• RQ1 How can intelligent multi-agent systems effectively mitigate security and privacy threats in EHR systems across data collection, transmission, and storage levels?
• RQ2 What role do specialized intelligent agents play in improving access control, authentication, and secure communication in E-health systems?
• RQ3 How does the proposed IBAC model outperform existing EHR security models in terms of flexibility, scalability, and patient control?
• RQ4 In what ways does the integration of agents enhance real-time, secure, and role-based access to sensitive health data?
• RQ5 What are the key limitations of current EHR security models that the proposed agent-based framework addresses?

Key findings

• The proposed IBAC model effectively enhances EHR security by integrating intelligent agents across all access control phases, reducing vulnerability to unauthorized access.
• The system enables patient-centric control, allowing individuals to manage who accesses their health data, thereby improving trust and data ownership.
• The use of specialized agents (e.g., user interface, authentication, connection management) streamlines communication and improves usability and system efficiency.
• The framework outperforms existing models like CARE, Patient-Centered Multi-Agent Systems, and biometric-based methods by providing a unified, agent-driven approach for all security functions.
• The algorithmic logic for access control ensures that only authenticated users with valid policies gain access, significantly reducing the risk of data leakage or tampering.
• The model demonstrates higher performance in securing health data compared to existing techniques, particularly in dynamic, real-time healthcare environments.