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Journal ArticleDOI

Building the wall: Addressing cybersecurity risks in medical devices in the U.S.A. and Australia

Timothy Webb, +1 more
- 01 Aug 2017 - 
- Vol. 33, Iss: 4, pp 559-563
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TLDR
It is established that stakeholders have a shared responsibility to address cybersecurity threats that can affect medical devices and manufacturers and health care providers should consider identification, detection and prevention steps at the pre-market and post-market stages.
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This article is published in Computer Law & Security Review.The article was published on 2017-08-01. It has received 18 citations till now. The article focuses on the topics: Health care.

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Journal ArticleDOI

An Internet of Things-based health prescription assistant and its security system design

TL;DR: A model for an IoT-based health prescription assistant (HPA) which helps each patient to follow the doctors recommendations properly and a security system that ensures user authentication and protected access to resources and services are proposed.
Journal ArticleDOI

Artificial Intelligence Technologies and Related Urban Planning and Development Concepts: How Are They Perceived and Utilized in Australia?

TL;DR: Public perceptions of how AI technologies and their application areas in urban planning and development are perceived and utilized in the testbed case study of Australian states and territories are examined.
Journal ArticleDOI

The state of research on cyberattacks against hospitals and available best practice recommendations: a scoping review

TL;DR: The objective of this study was to map the available literature on cyberattacks on hospitals and to identify the different domains of research, while extracting the recommendations and guidelines put forth in the literature.
Journal ArticleDOI

Cyber Risk in Health Facilities: A Systematic Literature Review

TL;DR: The research outlines the need to empirically investigate the cyber risk in the healthcare sector, giving a practical solution to health facilities, and highlights the poor attention of the scientific community on this topic except in the United States.
Journal ArticleDOI

A Feature Extraction Method of Hybrid Gram for Malicious Behavior Based on Machine Learning

TL;DR: A novel feature extraction method of hybrid gram (H-gram) with cross entropy of continuous overlapping subsequences is proposed, which implements semantic segmentation of a sequence of API calls or instructions and is more effective than the fixed-length n-gram in all four performance indexes of the classification algorithms.
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