| Autor: |
Devi, S. Siamala, Kuruba, Chandrakala, Yunyoung Nam, Abouhawwash, Mohamed |
| Předmět: |
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| Zdroj: |
Computer Systems Science & Engineering; 2023, Vol. 44 Issue 3, p2209-2223, 15p |
| Abstrakt: |
Health care visualization through Internet of Things (IoT) over wireless sensor network (WSN) becomes a current research attention due to medical sensor evolution of devices. The digital technology-based communication system is widely used in all application. Internet of medical thing (IoMT) assisted healthcare application ensures the continuous health monitoring of a patient and provides the early awareness of the one who is suffered without human participation. These smart medical devices may consume with limited resources and also the data generated by these devices are large in size. These IoMT based applications suffer from the issues such as security, anonymity, privacy, and interoperability. To overcome these issues, data aggregation methods are the solution that can concatenate the data generated by the sensors and forward it into the base station through fog node with efficient encryption and decryption. This article proposed a well-organized data aggregation and secured transmission approach. The data generated by the sensor are collected and compressed. Aggregator nodes (AN) received the compressed data and concatenate it. The concatenated and encrypted data is forward to fog node using the enhanced Paillier cryptography-based encryption with Message Authentication code (MAC). Fog node extracts the forwarded data from AN using Fog message extractor method (FME) with decryption. The proposed system ensures data integrity, security and also protects from security threats. This proposed model is simulated in Network Simulator 2.35 and the evaluated simulation results proves that the aggregation with MAC code will ensures the security, privacy and also reduces the communication cost. Fog node usages in between Aggregator and base station, will reduce the cloud server/base station computational overhead and storage cost. The proposed ideology is compared with existing data aggregation schemes in terms of computational cost, storage cost, communication cost and energy cost. Cost of communication takes 18.7 ms which is much lesser than existing schemes. [ABSTRACT FROM AUTHOR] |
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