journal article·2022Open access

Wind Driven Optimization-Based Medical Image Encryption for Blockchain-Enabled Internet of Things Environment

C. S. S. Anupama, Raed Alsini, N. Supriya, E. Laxmi Lydia, Seifedine Kadry, Sang-Soo Yeo, Yongsung Kim

Computers, Materials & Continua· Volume 73· Issue 2

Abstract

Internet of Things (IoT) and blockchain receive significant interest owing to their applicability in different application areas such as healthcare, finance, transportation, etc. Medical image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public networks. This paper presents a new wind driven optimization algorithm based medical image encryption (WDOA-MIE) technique for blockchain enabled IoT environments. The WDOA-MIE model involves three major processes namely data collection, image encryption, optimal key generation, and data transmission. Initially, the medical images were captured from the patient using IoT devices. Then, the captured images are encrypted using signcryption technique. In addition, for improving the performance of the signcryption technique, the optimal key generation procedure was applied by WDOA algorithm. The goal of the WDOA-MIE algorithm is to derive a fitness function dependent upon peak signal to noise ratio (PSNR). Upon successful encryption of images, the IoT devices transmit to the closest server for storing it in the blockchain securely. The performance of the presented method was analyzed utilizing the benchmark medical image dataset. The security and the performance analysis determine that the presented technique offers better security with maximum PSNR of 60.7036 dB.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Chaos-based Image/Signal Encryption · Blockchain Technology Applications and Security · Advanced Steganography and Watermarking Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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