Newer post-COVID perspective: Teledental encryption by de-multiplexed perceptrons

Area of Science:

• Digital Health
• Biomedical Engineering
• Cybersecurity in Healthcare

Background:

• The COVID-19 pandemic has accelerated the adoption of Teledental services.
• Secure transmission of sensitive intraoral data is crucial for effective remote diagnosis.
• Gingivitis, a common dental disease, requires timely diagnosis and treatment, necessitating secure data handling.

Purpose of the Study:

• To propose an efficient and secure encryption mechanism for intraoral information in Teledental applications.
• To develop a novel perceptron-based system with de-multiplexing capabilities for secure data transmission.
• To ensure data integrity and confidentiality of patient information, specifically gingivitis data, in a post-COVID context.

Main Methods:

• A perceptron with de-multiplexing ability is devised for data transmission.
• A session key is generated using learning rules applied to perceptrons by both patient and dentist.
• Gingivitis data is fragmented and processed with individual header generation to obfuscate intruders.
• Security analysis includes Chi-square, Avalanche, and Strict Avalanche tests on partial data shares.
• Intruder confusion techniques involve character frequency, floating frequency, and autocorrelation analysis.

Main Results:

• The proposed encryption mechanism demonstrates efficient and secure transmission of intraoral data.
• Security tests (Chi-square, Avalanche, Strict Avalanche) yielded favorable outcomes compared to classical algorithms.
• Techniques employed effectively confused potential intruders regarding data originality.
• The system ensures high data integrity and confidentiality for sensitive dental information.

Conclusions:

• The developed perceptron-based encryption offers a robust solution for securing Teledental communications.
• This approach enhances the reliability and security of remote dental diagnostics, particularly for conditions like gingivitis.
• The proposed mechanism is a valuable advancement for Teledental services in the post-COVID era, ensuring patient data privacy.