IoMT based Embedded Systems for healthcare: A Confidentiality and Privacy Approach throught Key Generation and Steganography

In the realm of healthcare, IoMT-based Embedded Systems signify a transformative era for patient care and medical monitoring. This digital evolution, however, poses a significant challenge: securing sensitive health information against advanced cyber threats within the stringent resource confines of embedded IoMT devices. Addressing this challenge necessitates innovative solutions that blend robust security with operational efficiency. This paper presents a pioneering integration of dynamic key generation and steganography, developed in our prior research, to enhance the security of healthcare embedded systems without compromising performance. By leveraging a dynamic key generation algorithm, our approach innovatively applies this mechanism within a steganographic communication model. This method eliminates the need for a finite list of pre-shared keys, which are vulnerable to compromise and demand substantial memory, making them impractical for embedded IoMT devices. Instead, by dynamically generating unique keys for each communication session, our approach greatly enhances the security and privacy of transmitted health data. We explore the practical implementation of this integrated solution in embedded IoMT systems, demonstrating its effectiveness in ensuring data confidentiality and meeting resource constraints. The dynamic nature of the key generation ensures that each transmission is securely encrypted with a unique key, significantly reducing the risk of unauthorized data access. Additionally, this paper highlights our solution’s compliance with stringent healthcare data protection standards, such as HIPAA, underscoring its suitability for safeguarding patient information. By merging the strengths of dynamic key generation with steganographic techniques, this work introduces a scalable and secure communication model tailored for embedded IoMT devices in healthcare, setting a new standard for secure, efficient communication in the medical field. This integration not only addresses the critical security challenges in the healthcare IoT sector but also pioneers a novel strategy that ensures the confidentiality and integrity of patient data while accommodating the inherent limitations of embedded medical devices.