Abstract
The Internet of Things is made of diverse networked things (i.e., smart, intelligent devices) that are consistently interconnected, producing meaningful data across the network without human interaction. Nowadays, the Healthcare system is widely interconnected with IoT environments to facilitate the best possible patient monitoring, efficient diagnosis, and timely operate with existing diseases towards the patients. Concerning the security and privacy of the patient's information. This paper is focused on Secure surveillance mechanism for a medical healthcare system with enabled internet of Things (sensors) by intelligently recorded video summary into the server and keyframes image encryption. This paper is twofold. Firstly, a well-organized keyframe extraction mechanism is called to extract meaningful image frames (detected normal/abnormal activities keyframe) by the visual sensor with an alert sent to the concerned authority in the healthcare system. Secondly, the final decision about the happened activity with extracted keyframes to keep highly secure from any adversary, and we propose an efficient probabilistic and lightweight encryption algorithm. Our proposed mechanism verifies effectiveness through producing results, robustness in nature, minimum execution time, and comparatively secure than other images (keyframes) encryption algorithms. Additionally, this mechanism can reduce storage, bandwidth, required transmission cost, and timely analysis of happened activity from any adversary with protecting the privacy of the patient's information in the IoT enabled healthcare system.
Highlights
Nowadays, Internet of Things (IoT) is intended to nurture speedily due to the creation of information communication and might be supposed as a description of ubiquitous computing because of IoT extends replacement with the direct user involvement to the continuously interconnected collaborative working devices without human interaction [1]–[3]
Bitwise XOR operation performed to encrypt in each channel of color images [IR, IG, IB] separately with designed block scrambling to disperse adjacent-pixels into dissimilar positions rapidly, which is determined through the chaotic sequence. ‘‘Fig 4’’ is showing, three rounds of diffusion and block scrambling operations in which keyframe images are ensuring adequately encrypted data as a cipher-image without recognizing actual keyframes in the smart healthcare system
Without the appropriate secret key, no information about the original keyframe image can be obtained. ‘‘Fig 7 and 8’’ illustrates each sub-section from A to P, the chaotic sequence (CTC)-IES encrypted images are using keyframe extraction image for smart healthcare IoT system. ‘‘Fig 7’’ sub-section A and I is the plain image in which A is the plain image from regular hospital monitoring image and I is the standard test image Lena
Summary
Internet of Things (IoT) is intended to nurture speedily due to the creation of information communication and might be supposed as a description of ubiquitous computing because of IoT extends replacement with the direct user involvement to the continuously interconnected collaborative working devices (sensor connected devices) without human interaction [1]–[3]. It is relatively tough as well as time spent for a specialist to resourcefully extract actionable intelligence from the massive amount of surveillance data [16] It is required such a type of machinery that can collect all critical visual information separately by employing the high processing and communication abilities of smart. These mechanisms can intelligently select proper sight (views) from different locations (multi-views) surveillance records captured by the various IoT enabled sensors These can smoothly process visual data in real-time, and only informative (relevant) data send to concern authority for future usage. In this article, we emphasis to address such types of problems by using the intelligent system as well as power-efficient which can manage every sensor intelligently and autonomously to gather only the most relevant data in real-time and take appropriate action with respective scenarios In this way, this mechanism can be capable of reducing transmission costs and congested bandwidth consumptions.
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