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An Analytic Model for Reducing Authentication Signaling Traffic in an End-to-End Authentication Scheme
Shadi Nashwan1, Imad I H Nashwan2
1Computer Science Department, Jouf University, Sakaka 42421, Saudi Arabia.
Sensors (Basel, Switzerland)
|August 10, 2021
Summary
This study optimizes end-to-end authentication (E2EA) in healthcare by finding the ideal number of short-term authentication phases (SAP) to minimize signaling traffic costs. An analytic model determined the optimal value for
Area of Science:
- Healthcare technology
- Network security
- Information systems
Background:
- End-to-end authentication (E2EA) is crucial for secure healthcare communication between physicians, patients, and sensors.
- Existing E2EA schemes involve multiple authentication phases (long-term, short-term, sensor) with varying costs.
- Determining the optimal number of short-term authentication phases (m) is critical for balancing security and efficiency.
Purpose of the Study:
- To develop an analytic model for optimizing the E2EA scheme in healthcare.
- To minimize the authentication signaling traffic cost by determining the optimal value of 'm'.
Main Methods:
- Modeled authentication signaling traffic as a Poisson process.
- Derived an authentication signaling traffic cost function for the parameter 'm'.
- Analyzed the cost function using gamma, hypo-exponential, and exponential distributions for authentication residence time.
Main Results:
- An optimal value for 'm' was determined through numerical analysis of the derived cost function.
- The proposed model effectively balances security levels with minimized E2EA costs.
- The study provides a method to reduce signaling traffic in healthcare authentication.
Conclusions:
- The optimal 'm' value minimizes authentication signaling traffic costs in E2EA schemes.
- The analytic model offers a practical approach for optimizing healthcare authentication protocols.
- Efficient E2EA is vital for secure and cost-effective remote patient monitoring and telehealth.
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