A Dynamic Cyber Security Situational Awareness Framework for Healthcare ICT Infrastructures

The healthcare sectors have experienced a massive technical evolution over the past decade by integration of medical devices with IT at both physical and cyber level for a critical Health Care Information Infrastructure (HCII). HCII provides huge benefits for the health care service delivery but evolving digital interconnectivity among medical and IT devices has also changed the threat landscape. In particular, systems are now more exposed to the cyber-attacks due to sensitivity and criticality of patient health care information and accessibility of medical devices and this pose any potential disruption of healthcare service delivery. There is a need to enhance security and resilience of HCII. In this paper, we present a Cyber Security Situational Awareness Framework that aims to improve the security and resilience of the overall HCII. The framework aims to develop a novel dynamic Situational Awareness approach on the health care ecosystem. We consider bio inspired Swarm Intelligence and its inherent features with the main principles of the Risk and Privacy assessment and management and Incident handling to ensure security and resilience of healthcare service delivery

Emerging Digital Technologies in Patient Care: Dealing with connected, intelligent medical device vulnerabilities and failures in the healthcare sector

The integration of the Internet of Medical Things (IoMT) and Artificial Intelligence (AI) into clinical routines is significantly impacting organisational preparedness at the point of care, raising concerns not only about the resilience of the healthcare infrastructure, but also about how physicians, clinicians, and healthcare professionals respond to, manage, and reduce new risks associated with connected and intelligent medical devices in the interest of patient safety and care. The following report summarises findings from the workshop entitled Emerging Digital Technologies in Patient Care: Dealing with Connected, Intelligent Medical Device Vulnerabilities and Failures in the Healthcare Sector, held on 23 February 2023 at Goodenough College, London. The workshop was organised by members of the Reg-MedTech project, funded by the PETRAS National Centre of Excellence in IoT Systems Cybersecurity (EPSRC grant number EP/S035362/1), in collaboration with project partners at the BSI, the UK’s National Standards Body. Since October 2021, the Reg-MedTech project has investigated the extent to which current regulatory frameworks and standards address the critical cybersecurity, data governance, and algorithmic integrity risks posed by connected and intelligent medical devices. A critical finding from its ongoing research has been the need to develop standards, regulations, and policies that are better informed by the experiences of physicians, clinicians, and healthcare professionals dealing with software-based medical devices or software as a medical device (SaMD) in their day-to-day practice

Towards a resilience assurance model for robotic autonomous systems

yesApplications of autonomous systems are becoming increasingly common across the field of engineered systems from cars, drones, manufacturing systems and medical devices, addressing prevailing societal changes, and, increasingly, consumer demand. Autonomous systems are expected to self-manage and self-certify against risks affecting the mission, safety and asset integrity. While significant progress has been achieved in relation to the modelling of safety and safety assurance of autonomous systems, no similar approach is available for resilience that integrates coherently across the cyber and physical parts. This paper presents a comprehensive discussion of resilience in the context of robotic autonomous systems, covering both resilience by design and resilience by reaction, and proposes a conceptual model of a system of learning for resilience assurance in a continuous product development framework. The resilience assurance model is proposed as a composable digital artefact, underpinned by a rigorous model-based resilience analysis at the system design stage, and dynamically monitored and continuously updated at run time in the system operation stage, with machine learning based knowledge extraction and validation

Identifying common problems in the acquisition and deployment of large-scale software projects in the US and UK healthcare systems

Public and private organizations are investing increasing amounts into the development of healthcare information technology. These applications are perceived to offer numerous benefits. Software systems can improve the exchange of information between healthcare facilities. They support standardised procedures that can help to increase consistency between different service providers. Electronic patient records ensure minimum standards across the trajectory of care when patients move between different specializations. Healthcare information systems also offer economic benefits through efficiency savings; for example by providing the data that helps to identify potential bottlenecks in the provision and administration of care. However, a number of high-profile failures reveal the problems that arise when staff must cope with the loss of these applications. In particular, teams have to retrieve paper based records that often lack the detail on electronic systems. Individuals who have only used electronic information systems face particular problems in learning how to apply paper-based fallbacks. The following pages compare two different failures of Healthcare Information Systems in the UK and North America. The intention is to ensure that future initiatives to extend the integration of electronic patient records will build on the ‘lessons learned’ from previous systems

Soft Actuators and Robotic Devices for Rehabilitation and Assistance

Soft actuators and robotic devices have been increasingly applied to the field of rehabilitation and assistance, where safe human and machine interaction is of particular importance. Compared with their widely used rigid counterparts, soft actuators and robotic devices can provide a range of significant advantages; these include safe interaction, a range of complex motions, ease of fabrication and resilience to a variety of environments. In recent decades, significant effort has been invested in the development of soft rehabilitation and assistive devices for improving a range of medical treatments and quality of life. This review provides an overview of the current state-of-the-art in soft actuators and robotic devices for rehabilitation and assistance, in particular systems that achieve actuation by pneumatic and hydraulic fluid-power, electrical motors, chemical reactions and soft active materials such as dielectric elastomers, shape memory alloys, magnetoactive elastomers, liquid crystal elastomers and piezoelectric materials. Current research on soft rehabilitation and assistive devices is in its infancy, and new device designs and control strategies for improved performance and safe human-machine interaction are identified as particularly untapped areas of research. Finally, insights into future research directions are outlined

Soft Actuators and Robotic Devices for Rehabilitation and Assistance

Soft actuators and robotic devices have been increasingly applied to the field of rehabilitation and assistance, where safe human and machine interaction is of particular importance. Compared with their widely used rigid counterparts, soft actuators and robotic devices can provide a range of significant advantages; these include safe interaction, a range of complex motions, ease of fabrication and resilience to a variety of environments. In recent decades, significant effort has been invested in the development of soft rehabilitation and assistive devices for improving a range of medical treatments and quality of life. This review provides an overview of the current state-of-the-art in soft actuators and robotic devices for rehabilitation and assistance, in particular systems that achieve actuation by pneumatic and hydraulic fluid-power, electrical motors, chemical reactions and soft active materials such as dielectric elastomers, shape memory alloys, magnetoactive elastomers, liquid crystal elastomers and piezoelectric materials. Current research on soft rehabilitation and assistive devices is in its infancy, and new device designs and control strategies for improved performance and safe human-machine interaction are identified as particularly untapped areas of research. Finally, insights into future research directions are outlined

Resilient Linear Classification: An Approach to Deal with Attacks on Training Data

Data-driven techniques are used in cyber-physical systems (CPS) for controlling autonomous vehicles, handling demand responses for energy management, and modeling human physiology for medical devices. These data-driven techniques extract models from training data, where their performance is often analyzed with respect to random errors in the training data. However, if the training data is maliciously altered by attackers, the effect of these attacks on the learning algorithms underpinning data-driven CPS have yet to be considered. In this paper, we analyze the resilience of classification algorithms to training data attacks. Specifically, a generic metric is proposed that is tailored to measure resilience of classification algorithms with respect to worst-case tampering of the training data. Using the metric, we show that traditional linear classification algorithms are resilient under restricted conditions. To overcome these limitations, we propose a linear classification algorithm with a majority constraint and prove that it is strictly more resilient than the traditional algorithms. Evaluations on both synthetic data and a real-world retrospective arrhythmia medical case-study show that the traditional algorithms are vulnerable to tampered training data, whereas the proposed algorithm is more resilient (as measured by worst-case tampering)

The visible and the invisible: Distributed Cognition for medical devices

Many interactive medical devices are less easy to use than they might be, and do not fit as well as they could in their contexts of use. Occasionally, the deficiencies lead to serious incidents; more often, they have a less visible effect on the resilience and efficiency of healthcare systems. These issues remain largely invisible as they are not reported and have rarely been studied. In this paper, we report on the use of DiCoT as an approach to representing and reasoning about medical work, and about the role of device design within that work. We focus in particular on the design and use of infusion devices. This work highlights the value of observational studies for engineering interactive medical devices, and illustrates the value of a systematic approach to gathering and analyzing qualitative data