Attackers increase the length of transmit packets intentionally in order to degrade the network resources. In this paper, ping of death as a cyber security attack is modeled for IoT networks. Internet of things (IoT) is almost vulnerable to cyber security attacks due to the limited computational resources of conventional IoT devices. Moreover, once alerted by the system about the high risk status of a patient, a doctor can fetch all the health records of the patient for a specified period, which can be utilized for a detailed clinical diagnosis. The proposed system is also associated with a mobile app that enables the continuous monitoring of the health status of the patients. The collected data are analyzed through fuzzy logic in edge devices to efficiently identify the risk status (such as low risk, moderate risk and high risk) of the COVID19 patients in real time. The health data are collected through sensors attached to the patients and transmitted to the edge devices and cloud storage for further processing.
The proposed model makes use of the IoMT architecture to collect real time biological data (or health information) from the patients to monitor and analyze the health conditions of the infected patients and generates alert messages that are transmitted to the concerned parties such as relatives, medical staff and doctors to provide appropriate treatment in a timely fashion.
In this paper, a real time health monitoring system for COVID19 patients based on edge computing and fuzzy logic technique is proposed. Several smart-healthcare systems based on the Internet of Medical Things (IoMT) have attracted worldwide interest in their growing technical assistance in health services, notably in predicting, identifying and preventing, and their remote surveillance of most infectious diseases. Any modern method that allows for speedy and efficient monitoring of COVID19-affected patients could be highly beneficial to medical staff. In the era of an extraordinary public health crisis due to the spread of the novel coronavirus (2019-nCoV), which caused the deaths of millions and affected a multitude of people worldwide in different ways, the role of smart healthcare has become indispensable. Smart healthcare is an integral part of a smart city, which provides real time and intelligent remote monitoring and tracking services to patients and elderly persons. We believe the framework presented in this chapter will provide a new direction to developers and stakeholders in implementing an efficient and secure smart city. Furthermore, a threat model is presented that identifies the potential attacks at each layer so that the developers can incorporate specific protection mechanisms. The security mechanisms can be embedded in each layer leading to more protection at each level. The layered approach not only improves the management but also improves the overall security of smart city systems. These layers comprise Application, Communication, Infrastructure, Data, and Stakeholders (ACIDS). This chapter aims at proposing a framework for the smart city which segregates it into five layers. Due to its interconnected nature, the architecture is highly prone to cyber-attacks. A successful smart city architecture builds on an interconnected relationship of smart applications. Smart city applications provide ease in carrying out daily chores of citizens as well as facilitate governments in controlling the whole city.
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