RETRACTED: Internet of Things with Artificial Intelligence for Health Care Security (Retracted Article)

被引:20
作者
Ghazal, Taher M. [1 ,2 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Ctr Cyber Secur, Bangi 43600, Selangor, Malaysia
[2] Univ City Sharjah, Skyline Univ Coll, Sch Informat Technol, Sharjah 1797, U Arab Emirates
关键词
Technology; Wireless; Dashboard; Encrypted; Patient; Database; Artificial Intelligence; FRAMEWORK; SYSTEM;
D O I
10.1007/s13369-021-06083-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In recent years, health care facilities are moving towards technological advancements for precise patient monitoring and record management. Though it is technically advanced, the health care information and communication technology network's security is a significant challenge for health care. With the aid of standard algorithms, unstructured data existing outside organized databases (i.e., electronic documents and reports) is difficult to arrange and secure. The existing clustering method has a disadvantage of efficiency issues for recovering data transfer. This paper proposes the Internet of Things with Artificial Intelligence System (IoT-AIS) for health care security. Wireless sensor networks are developed by IoT technology. IoT network is used to bridge the physical and digital world. IoT-AIS is used to monitor the patient's data and encrypt them. The encrypted data are stored in the cloud to maintain the patient data to access remotely. The IoT-AIS dashboard provides an individualized user interface for individual patients to maintain their records individually with single-user access. The proposed paper's simulation analysis proved that the Patient Record of health care could be encrypted and provide individualized access. The experimental results of IoT-AIS achieve the highest data transmission rate to 98.14% and the highest delivery rate of (98.90%), high period of standard responses (93.79%), less delay estimation (10.76%), improved throughput (98.23%), effective bandwidth monitoring (83.14%) energy usage (8.56%) and highest performance rate (98.4%) when compared to other methods.
引用
收藏
页码:5689 / 5689
页数:1
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