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Sustainable smart city initiatives significantly improve the living standards of citizens and bring significant changes in economic, environmental, and social well-being. Sustainable and remote medical services are vital attributes of modern smart health infrastructure. Smart remote health infrastructure uses interconnected devices to gather and exchange health data. In smart health infrastructure, massive quantities of health data are gathered as Personal Health Records (PHR). Clinical images form a major part of the accumulated PHR. As medical images are confidential and sensitive, secure storage and transmission are significant. Hence, different cryptographic techniques are used to enhance medical image security. The conventional cryptographic schemes are complex and generate a single cipher image corresponding to a plain image. The cipher images are stored in a single database. Such storage makes the cryptosystem weak against single-point attacks. This paper discusses a simple, keyless, and distributed secure storage mechanism for medical images called SecMISS. SecMISS uses Random Grid-based Visual Secret Sharing (RGVSS) along with super-resolution for secure encryption with distributed storage and better reconstruction. The security parameters such as SSIM (≈ 0), correlation of adjacent pixels (≈ 0), PSNR (≤ 8 dB), and entropy (= 1) between share and initial image show that SecMISS provides highest level of security. Similarly, different Human Visual System (HVS) parameters between the initial and reconstructed images show an improvement in the reconstruction. Experimental results show that SecMISS outperforms the existing technique in terms of security and reconstruction. Thereby SecMISS can be efficiently used for securing medical image in sustainable smart hospitals and health infrastructures. [ABSTRACT FROM AUTHOR]

Social Internet of Things (SIoT) is one of the emerging research areas which integrates the Internet of Things (IoT) with social networking concepts. It envisages better information sharing, by overcoming the scalability issues in IoT. It is supposed to overhaul the smart health industry, as it is a flexible compared to conventional IoT based solutions. It however poses many challenges with data authentication and privacy, being a couple of such issues that need to be addressed. In this paper, we present an efficient watermarking method for tamper detection, localization, and self-recovery of medical images for SIoT-based smart health networks. The cover image is initially divided into four equal parts, with each part progressively divided into 4 × 4 non-overlapping blocks. A watermark is prepared from a group of randomly chosen four, 4 × 4 blocks, determined by chaotic mapping. The information is embedded into 4 sub-blocks mapped utilizing chaotic sequence such that the restoration process can be carried out even if three sub-blocks out of four containing the information, get tampered with. The proposed technique is found to restore almost 1/3rd of the tampered image and produces a high-quality image with the average Peak Signal-to-Noise Ratio value of above 33 dB after the restoration process. The performance of the proposed method for various collage attacks shows its efficacy over other state-of-the-art techniques making it a potential candidate for SIoT driven smart health systems. [ABSTRACT FROM AUTHOR]