Formulating an Advanced Security Protocol for Internet of Medical Things based on Blockchain and Fog Computing Technologies

The Internet of Medical Things (IoMT) is an evolving field in healthcare that connects medical devices to the Internet to enable efficient data sharing and health information collection. The IoMT aims to improve the quality of healthcare, facilitate diagnosis and treatment, and enhance patient safety. Nonetheless, the IoMT networks are usually exposed to multiple security attacks. Also, recent studies indicate that security protocols contain flaws in protecting patient data. Thus, data must be protected by innovative security protocols. In our work, we propose a Medical Security Protocol (MedSecP) to support security in IoMT. The proposed protocol adopts the Twofish encryption, Naive Bayes (NB), and decision tree (DT) within the private blockchain (PBC) Fog Computing (FC) to build robust security procedures. The Twofish encryption algorithm is used to provide medical information concealment. In our proposed protocol, the type of data is first determined, and accurate and appropriate medical decisions are made based on the collected data using a decision tree algorithm, and then rapid classification of the patient data is done using the Naive Bayes algorithm. Confidential medical data is then encrypted using the Twofish algorithm to ensure the confidentiality of this data and prevent unauthorized access. Finally, this encrypted medical data is stored using blockchain technology. Twofish, NB, and DT are organized to work harmoniously with the PBC. The latter manages and distributes data peer-to-peer in IoMT. We leverage Fog Computing to speed up decision-making without resorting to the remote cloud. We analyzed our protocol in terms of security and performance. Our results indicate that MedSecP provides reliable security against attacks as the protocol demonstrated an average security attack response rate of 97.20%, demonstrating its resistance to external threats by keeping the encrypted medical data, classified and achieving appropriate medical decisions. In terms of performance, MedSecP has demonstrated an average security response time of around 50ms, providing fast and efficient performance. In MedSecP, the highest value for encryption is 0.000015 ms, and decryption is 0.000017 ms when applying the Twofish algorithm which is considered extremely suitable for implementing health systems operations compared to existing encryption algorithms. Consequently, MedSecP provides lightweight operations in support of complex security measures that qualify it to support healthcare institutions. © 2024 College of Education, Al-Iraqia University. All rights reserved.