Affiliations: [a] School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| [b] School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China
| [c] Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia
| [d] College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia
Correspondence:
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Corresponding authors. Jalaluddin Khan and Jian Ping Li, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. E-mail: E-mail: jalal4amu@yahoo.com (Jalaluddin Khan); E-mail: E-mail: jpli2222@uestc.edu.cn (Jian Ping Li).
Abstract: The emerging technologies with IoT (Internet of Things) systems are elevated as a prototype and combination of the smart connectivity ecosystem. These ecosystems are appropriately connected in a smart healthcare system which are generating finest monitoring activities among the patients, well-organized diagnosis process, intensive support and care against the traditional healthcare operations. But facilitating these highly technological adaptations, the preserving personal information of the patients are on the risk with data leakage and privacy theft in the current revolution. Concerning secure protection and privacy theft of the patient’s information. We emphasized this paper on secure monitoring with the help of intelligently recorded summary’s keyframe extraction and applied two rounds lightweight cosine-transform encryption. This article includes firstly, a regimented process of keyframe extraction which is employed to retrieve meaningful frames of image through visual sensor with sending alert (quick notice) to authority. Secondly, employed two rounds of lightweight cosine-transform encryption operation of agreed (detected) keyframes to endure security and safety for the further any kinds of attacks from the adversary. The combined methodology corroborates highly usefulness with engendering appropriate results, little execution of encryption time (0.2277-0.2607), information entropy (7.9996), correlation coefficient (0.0010), robustness (NPCR 99.6383, UACI 33.3516), uniform histogram deviation (R 0.0359, G 0.0492, B 0.0582) and other well adopted secure ideology than any other keyframe or image encryption approaches. Furthermore, this incorporating method can effectively reduce vital communication cost, bandwidth issues, storage, data transmission cost and effective timely judicious analysis over the occurred activities and keep protection by using effective encryption methodology to remain attack free from any attacker or adversary, and provide confidentiality about patient’s privacy in the smart healthcare system.
Keywords: Internet of things, security, privacy, secure surveillance, image encryption
