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Improving security performance of healthcare data in the Internet of medical things using a hybrid metaheuristic model

Ashok Kanneboina, Gopikrishnan Sundaram

International Journal of Applied Mathematics and Computer Science

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2023

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Vol. 33, no. 4

623--636

EN

Internet of medical things (IoMT) network design integrates multiple healthcare devices to improve patient monitoring and real-time care operations. These networks use a wide range of devices to make critical patient care decisions. Thus, researchers have deployed multiple high-security frameworks with encryption, hashing, privacy preservation, attribute based access control, and more to secure these devices and networks. However, real-time monitoring security models are either complex or unreconfigurable. The existing models’ security depends on their internal configuration, which is rarely extensible for new attacks. This paper introduces a hybrid metaheuristic model to improve healthcare IoT security performance. The blockchain based model can be dynamically reconfigured by changing its encryption and hashing standards. The proposed model then continuously optimizes blockchain based IoMT deployment security and QoS performance using elephant herding optimization (EHO) and grey wolf optimization (GWO). Dual fitness functions improve security and QoS for multiple attack types in the proposed model. These fitness functions help reconfigure encryption and hashing parameters to improve performance under different attack configurations. The hybrid integration of EH and GW optimization models can tune blockchain based deployment for dynamic attack scenarios, making it scalable and useful for real-time scenarios. The model is tested under masquerading, Sybil, man-in-the-middle, and DDoS attacks and is compared with state-of-the-art models. The proposed model has 8.3% faster attack detection and mitigation, 5.9% better throughput, a 6.5% higher packet delivery ratio, and 10.3% better network consistency under attack scenarios. This performance enables real-time healthcare use cases for the proposed model.

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A multi-agent architecture for interoperable medical information systems

Zarour K., Zarour N.

Journal of Medical Informatics & Technologies

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2010

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Vol. 15

73--79

EN

The Medical information systems evolve constantly. The quality of the medical information system relies on competences, qualifications, and the organization of the participating partners. Those last ones belong to heterogeneous and autonomous information systems. So, it is necessary to assure a permanent cooperation. This paper shows a coherent architectural framework that allows the development of interoperable medical information systems in measure or these systems evolve. The essential idea is to use concepts of multi-agent systems to perform the different activities of medical information system and thus, to adapt the solutions provided by the agent paradigm to solve the different problems encountered while establishing a medical information system.

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Tasks and applicable technologies in computer aided nephrology

Filutowicz Z., Filutowicz J., Szczepaniak P. S., Niewiadomski A.

Journal of Medical Informatics & Technologies

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2001

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Vol. 2, Part. 2

SN3--SN7

EN

Dealing with the problem of co-ordination of subjects involved in kidney transplantation the paper displays new possibilities of using complex information systems for integration of dialysis centres and specialised health care units. Growing requirements of information system customers and development of object modeling methods stimulate creation of complex information systems designed to assist the work of medical staff. In the system presented in the paper information needs of customers are modeled by means of UML diagrams and the system itself involves a number of computer technologies, like inference in uncertainty conditions, artificial intelligence algorithms, knowledge bases, distributed processing, and Internet techniques. The system implementation covers numerous functional modules which are necessary to ensure efficient assistance of medical staff in their work, to improve the quality of patients’ life, and to carry out research in the fields of medicine and computer science.