Cybersecurity indexes for eHealth
- Burke, Wendy, Oseni, Taiwo, Jolfaei, Alireza, Gondal, Iqbal
- Authors: Burke, Wendy , Oseni, Taiwo , Jolfaei, Alireza , Gondal, Iqbal
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 2019 Australasian Computer Science Week Multiconference, ACSW 2019; Sydney, Australia; 29th-31st January 2019 p. 1-8
- Full Text: false
- Reviewed:
- Description: This study aimed to explore the cybersecurity landscape to identify cybersecurity indexes that may be relevant to the health industry. While the healthcare sector poses security concerns regarding patients' records, cybersecurity in the healthcare sector has not been given much consideration. Cybersecurity indexes are a survey that measures security preparedness and capabilities of a country or organisation. An index is made up of a series of questions, often broken into categories. These categories target areas such as law, technical responses, organisational threats, capacity building and social context. Some indexes provide ranking capabilities against other countries, while others directly evaluate what it means to be cyber-ready. In this paper, cybersecurity indexes were reviewed regarding the level of assessment (country level/organisation level), and their consideration of the wider community, the health sector, and their appearance in academic literature. Results from this study found that there was no consistency between the indexes investigated, with each index having a diverse number of categories and indicators. Some indexes resulted in a score; others did not rank their results in league tables. Evidence to calculate the level of adherence was often obtained from secondary sources, with four of the country indexes using both primary and secondary sources. Eight (out of fourteen) indexes measured wider community indicators and only one index specifically measured eHealth services. Findings from the initial systematic review suggest that hardly any peer-reviewed journal articles exist on the topic of cybersecurity indexes. The paper concludes that most of the indexes studied are broad and do not consider the eHealth sector specifically. Each index relies on a different process to gauge cybersecurity, with little to no academic rigour. It is expected that this research will contribute to the current (limited) literature addressing cybersecurity indexes.
- Description: ACM International Conference Proceeding Series
A patient agent controlled customized blockchain based framework for internet of things
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
- Authors: Uddin, Md Ashraf
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.
- Description: Doctor of Philosophy
- «
- ‹
- 1
- ›
- »