# SVIoT: A Secure Visual-IoT Framework for Smart Healthcare
## 1 Introduction  
The technological advances in communication and networking infrastructure in the past few decades have resulted in an exponential increase in digitization. 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 smart-healthcare, smart home, smart industry, etc. [1, 2]. 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]. Unfortunately, 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]. According to the Protenus Breach Barometer, more than 40 million patient data records were breached in 2021, of which 8 million records were breached by insiders, and 758 breaches were incidental [5]. In addition, it was reported that there was a 42% hike in these data breaches compared to the previous year [5]. The situation, therefore, demands the development of comprehensive security, privacy, and authentication solutions for IoT-driven systems, owing to their dynamic and resource-constrained nature. One of the common solutions adopted is the revisitation of various well know encryption algorithms to develop their lightweight counterparts for IoT-based platforms. However, given the nature and magnitude of security issues, the development of sustainable security solutions for critical applications, such as health care and smart cities, is of the utmost importance [6; 7]. One of the possible solutions that has attracted attention is the embedding of information in images. This technology not only provides security, but is also capable of exactly identifying a node in a distributed computing scenario, such as IoT-driven networks, e.g., smart-health in a smart city. An IoT-driven smart-health setup is presented in Figure 1.  
As described in Figure 1, multiple devices are needed to exchange the Electronic Medical Record (EMR) for proper diagnosis/treatment remotely. The EMR, related to a particular medical condition, is collected through various devices and sensors monitoring the patient. Instead of transmitting the EMR through a highly insecure network, the information hiding technology embeds the EMR in the patient's medical imagery, to put the adversary at bay. The transmitted imagery-containing data are received by different authentic receivers for diagnosis and prescription. Information hiding has been widely studied in both academia and industry in recent years. The main research directions for data hiding include copyright identification, data integrity, authentication, tamper recovery, retrieval of original images, and covert communication [8; 9; 10]. Information hiding could be reversible, as well as irreversible. Reversible hiding is suitable for applications such as smart-health, etc., where recovery of the cover image at the receiver is important [11; 12; 13]. One of the main challenges in RDH is the payload. Many high-payload RDH solutions, based on interpolation, exist; however, the techniques based on Image interpolation add significant redundancy, making them unfit for resource-constrained platforms such as IoT, as they require more storage space/bandwidth. In this paper, we present SVIoT, which makes use of novel One Dimensional Neighbor Mean Interpolation (ODNMI). The use of ODNMI in SVIoT reduces the computational complexity and storage/bandwidth requirement by 50%.