Attack-Graph Threat Modeling Assessment of Ambulatory Medical Devices

Luckett, Patrick; McDonald, J. Todd; Glisson, William Bradley

doi:10.24251/hicss.2017.441

Cited by 19 publications

(16 citation statements)

References 36 publications

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“…Researchers are continuously demonstrating that medical devices are at risk from a security perspective [17][18][19][20][21]. Malasri and Wang [17] examined the insecurity of implantable medical devices, such as pacemakers.…”

Section: Related Workmentioning

confidence: 99%

A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices

Grispos¹,

Glisson

Cooper

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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The integration of medical devices in everyday life prompts the idea that these devices will increasingly have evidential value in civil and criminal proceedings. However, the investigation of these devices presents new challenges for the digital forensics community. Previous research has shown that mobile devices provide investigators with a wealth of information. Hence, mobile devices that are used within medical environments potentially provide an avenue for investigating and analyzing digital evidence from such devices.The research contribution of this paper is twofold. First, it provides an empirical analysis of the viability of using information from smartphone applications developed to complement a medical device, as digital evidence. Second, it includes documentation on the artifacts that are potentially useful in a digital forensics investigation of smartphone applications that interact with medical devices.

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Section: Related Workmentioning

confidence: 99%

A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices

Grispos¹,

Glisson

Cooper

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Despite these factors, the papers covered important and interesting topics. Luckett, McDonald, and Glisson (2017) studied ambulatory medical devices with modeled cyberattack graphs to assess these devices' potential security threat. De Mooy and Yuen (2017) conducted a qualitative research study using grounded theory to analyze data from the research and development of Fitbit wearables.…”

Section: Hit Privacy and Security For Health Information Systemsmentioning

confidence: 99%

The Trajectory of IT in Healthcare at HICSS: A Literature Review, Analysis, and Future Directions

Samhan¹,

Crampton²,

Ruane³

2018

CAIS

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Research has extensively demonstrated that healthcare industry has rapidly implemented and adopted information technology in recent years. Research in health information technology (HIT), which represents a major component of the Hawaii International Conference on System Sciences, demonstrates similar findings. In this paper, review the literature to better understand the work on HIT that researchers have conducted in HICSS from 2008 to 2017. In doing so, we identify themes, methods, technology types, research populations, context, and emerged research gaps from the reviewed literature. With much change and development in the HIT field and varying levels of adoption, this review uncovers, catalogs, and analyzes the research in HIT at HICSS in this ten-year period and provides future directions for research in the field.

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“…In addition to the benefits, technology exposes healthcare to the risks that are inherent to digital settings, which fosters an environment that is conducive to adversarial cyberattacks [4][5][6]. These concerns are being raised by practitioners [7], the government [8], and academics [6,[9][10][11][12][13][14][15] for medical equipment and any devices that communicate with this equipment.…”

Section: Introductionmentioning

confidence: 99%

Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices

Hodges¹,

McDonald

Glisson

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The escalating integration of network-enabled medical devices raises concerns for both practitioners and academics in terms of introducing new vulnerabilities and attack vectors. This prompts the idea that combining medical device data, security vulnerability enumerations, and attack-modeling data into a single database could enable security analysts to proactively identify potential security weaknesses in medical devices and formulate appropriate mitigation and remediation plans. This study introduces a novel extension to a relational database risk assessment framework by using the open-source tool OVAL to capture device states and compare them to security advisories that warn of threats and vulnerabilities, and where threats and vulnerabilities exist provide mitigation recommendations. The contribution of this research is a proof of concept evaluation that demonstrates the integration of OVAL and CAPEC attack patterns for analysis using a database-driven risk assessment framework.

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Attack-Graph Threat Modeling Assessment of Ambulatory Medical Devices

Abstract: Abstract

Cited by 19 publications

References 36 publications

A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices

A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices

The Trajectory of IT in Healthcare at HICSS: A Literature Review, Analysis, and Future Directions

Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices

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