Work

Modular inverse visual cryptography for balancing security, quality, and efficiency in image transmission

Year: 2025

Type: article

Abstract: In this article, a new Inverse Module Visual Cryptography (IMVC) system is proposed to transmit a small computed tomography (CT) scan image over the IoT network securely and efficiently. In particular, Internet of Things (IoT) devices are important for the healthcare industry as they transmit sensitive imaging data; thus, confidentiality and high image fidelity are critical. The IMVC framework stands as a blend between visual cryptography and the very efficient and light-weighted modular arithmetic, suitable for mostly computational-constrained IoT networks. In this way, CT scan images are divided into pixel-aligned shares, inserted into cover images, and securely sent to destinations of the receiver. Expected outcome shows that the IMVC reconstructs equally a complete and lossless image, which displays equal quality parameters such as an infinite peak signal to noise ratio (PSNR) and equal mean square error (MSE) of zero, signifying the reconstructed images were accurate. Furthermore, expected high immunity to brute-force, statistical, and collusion attacks makes the methodology more reliable for improving the security of the IoT-based medical application. As conceived, performance tests are expected to report an efficient computational building and time required to encrypt and decrypt the framework, which will amount to an average of 1.79 and 0.45 s, respectively, implying real-time suitability of the framework in clinical settings. In this work, the proposed IMVC allows for the development of a feasible and effective solution for secure transfer of important image data in an IoT healthcare context, while addressing the requirements of security, image quality, as well as efficient transmission.

Source: PeerJ Computer Science

DOI: 10.7717/peerj-cs.3140

Authors: Selva Mary, John Blesswin, Suresh Sankaranarayanan, Abdul Rahaman Wahab Sait

Institutions: SRM Institute of Science and Technology, King Faisal University

Language: English

Topic: Chaos-based Image/Signal Encryption

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,395