ABSTRACT
The emergence of pandemic diseases like Covid-19 in recent years has made it more important for Internet of Medical Things (IoMT) environments to build contact between patients and doctors in order to control their health state. Patients will be able to send their healthcare data to the cloud server of the medical service provider in remote medical environments through sensors connected to their smart devices, such as watches or smartphones. However, patients' worries surrounding their data privacy protection are still present. In order to ensure the security and privacy of patients' healthcare data in remote medical environments, a number of different schemes have been proposed by researchers. However, these schemes have not been able to take all security requirements into account. Consequently, in this study, we have proposed a secure and effective protocol to safeguard the privacy of patients' medical data when it is sent to the server. This protocol entails two components: mutual authentication of the patient and the server of the medical service provider, as well as the integrity of the exchanged data. Also, our scheme satisfies security requirements and is resistant to well-known attacks. Following this, we used the Scyther tool to formally analyze our proposed scheme. The results showed that the scheme is secure, and in the section on performance analysis, we demonstrated that the proposed scheme performs better than comparable schemes. © 2023 IEEE.
ABSTRACT
Due to the global COVID-19 pandemic, interest in non-face-to-face telehealth is increasing worldwide, and telehealth services are being activated in various fields. In some countries, successful cases of remote surgery using non-face-to-face telehealth services are emerging one after another. Due to the absence of related standards presented to precisely handle security requirements in a non-face-to-face telehealth environment, security threats in telehealth are proceeding in a form that relies entirely on IT technology. However, the IT technology used in the medical environment is somewhat different from the existing ICT technology, so the need for a cybersecurity framework for non-face-to-face telehealth is becoming a much more important issue. This paper focuses on what needs to be considered to establish an appropriate security model in non-face-to-face telehealth. © 2022 IEEE.
ABSTRACT
The challenge of meeting security requirements (of a nation-state) and the privacy needs of citizens is perhaps a political goal, but it is enabled by technology. Attacks on citizens tend to move the balance towards security, whilst civil liberties groups often act as a counter to not over-correct security, so as to guarantee privacy. This paper explores Australian attitudes towards privacy and surveillance during the pandemic. We consider a fundamental question: Has the pandemic changed the perception of Australian citizens with regard to their fundamental right to privacy? We surveyed Australian attitudes to privacy in the light of the COVID-19 pandemic and report on some interesting results. © 2022, IFIP International Federation for Information Processing.
ABSTRACT
Airport operations are undergoing significant change, having to meet pandemic requirements in addition to intrinsic security requirements. Although air traffic has declined massively, airports are still the critical hubs of the air transport network. The new restrictions due to the COVID-19 pandemic pose new challenges for airport operators in redesigning airport terminals and managing passenger flows. To evaluate the impact of COVID-19 restrictions, we implement a reference airport environment. In this reference Airport in the Lab environment we will demonstrate the operational consequences derived from the new operational requirements. In addition, countermeasures to mitigate any negative impacts of these changes are tested. The results highlight emerging issues that the airport will most likely face and possible solutions. Finally, we could apply the findings and lessons learned from our testing at our reference airport to a real airport. © 2021 IEEE.
ABSTRACT
First responders and other forward deployed essential workers can benefit from advanced analytics. Limited network access and software security requirements prevent the usage of standard cloud based microservice analytic platforms that are typically used in industry. One solution is to precompute a wide range of analytics as files that can be used with standard preinstalled software that does not require network access or additional software and can run on a wide range of legacy hardware. In response to the COVID-19 pandemic, this approach was tested for providing geo-spatial census data to allow quick analysis of demographic data for better responding to emergencies. These data were processed using the MIT SuperCloud to create several thousand Google Earth and Microsoft Excel files representative of many advanced analytics. The fast mapping of census data using Google Earth and Microsoft Excel has the potential to give emergency responders a powerful tool to improve emergency preparedness. Our approach displays relevant census data (total population, population under 15, population over 65, median age) per census block, sorted by county, through a Microsoft Excel spreadsheet (xlsx file) and Google Earth map (kml file). The spreadsheet interface includes features that allow users to convert between different longitude and latitude coordinate units. For the Google Earth files, a variety of absolute and relative colors maps of population density have been explored to provide an intuitive and meaningful interface. Using several hundred cores on the MIT SuperCloud, new analytics can be generated in a few minutes. © 2021 IEEE.