Abstract
The advancement of the Internet of Things (IoT) has transfigured the overlay of the physical world by superimposing digital information in various sectors, including smart cities, industry, healthcare, etc. Among the various shared information, visual data are an insensible part of smart cities, especially in healthcare. As a result, visual-IoT research is gathering momentum. In visual-IoT, visual sensors, such as cameras, collect critical multimedia information about industries, healthcare, shopping, autonomous vehicles, crowd management, etc. In healthcare, patient-related data are captured and then transmitted via insecure transmission lines. The security of this data are of paramount importance. Besides the fact that visual data requires a large bandwidth, the gap between communication and computation is an additional challenge for visual IoT system development. In this paper, we present SVIoT, a Secure Visual-IoT framework, which addresses the issues of both data security and resource constraints in IoT-based healthcare. This was achieved by proposing a novel reversible data hiding (RDH) scheme based on One Dimensional Neighborhood Mean Interpolation (ODNMI). The use of ODNMI reduces the computational complexity and storage/bandwidth requirements by 50 percent. We upscaled the original image from M × N to M ± 2N, dissimilar to conventional interpolation methods, wherein images are upscaled to 2M × 2N. We made use of an innovative mechanism, Left Data Shifting (LDS), before embedding data in the cover image. Before embedding the data, we encrypted it using an AES-128 encryption algorithm to offer additional security. The use of LDS ensures better perceptual quality at a relatively high payload. We achieved an average PSNR of 43 dB for a payload of 1.5 bpp (bits per pixel). In addition, we embedded a fragile watermark in the cover image to ensure authentication of the received content.
Highlights
The emergence of new technological concepts, such as the Visual Internet of Things (VIoT) and cloud computing has forced the potential applicability of technology in areas such as smarthealthcare, smart home, smart industry, etc. [1,2]
We propose an One Dimensional Neighborhood Mean Interpolation (ODNMI) scheme, with a special focus on reducing data redundancy leading to reduced storage space and bandwidth requirements, while maintaining reversibility, along with high embedding capacity
We developed a novel security mechanism, called SVIoT, for the transmission of patient information in an IoT-based healthcare setup
Summary
The technological advances in communication and networking infrastructure in the past few decades have resulted in an exponential increase in digitization. The present trend, in areas such as smart-health, is to collect the digitized information from numerous devices and/or IoT nodes and exchange said information through various networking platforms to achieve high-performance efficiency in terms of speed, resources, and cost factor [3]. Utilizing insecure networks, such as the internet, etc., for transferring critical data has been found to face continuous threats from the adversary. The threat of cyberattacks on privacy and data integrity faced by service providers has been on the rise. Take the example of the medical field; the data breaches associated with the healthcare sector have grown exponentially in recent years, and millions of health records are breached every year [4]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
