Abstract
Medical devices are complex cyber-physical systems incorporating emergent hardware and software components. However, this complexity leads to a wide attack surface posing security risks and vulnerabilities. Mitigation and management of such risks during premarket design and postmarket deployment are required. Dynamically mitigating threat potential in the presence of unknown vulnerabilities requires an adaptive risk-based scheme to assess the system's state, a secure system architecture that can isolate hardware and software components, and design methods that can adaptively adjust the system's topology based on risk changes. The essential complementary aspects during deployment are detecting, characterizing, and quantifying security threats. This article presents a dynamic risk management and mitigation approach based on probabilistic threat estimation. A smart-connected-pacemaker case study illustrates the approach. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Original language | English (US) |
---|---|
Article number | 8239935 |
Pages (from-to) | 38-43 |
Number of pages | 6 |
Journal | IEEE Software |
Volume | 35 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2017 |
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Keywords
- medical-device security
- risk assessment and management
- software development
- software engineering
- threat estimation
ASJC Scopus subject areas
- Software
Cite this
Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems. / Rao, Aakarsh; Carreon, Nadir; Lysecky, Roman L; Rozenblit, Jerzy W.
In: IEEE Software, Vol. 35, No. 1, 8239935, 01.01.2017, p. 38-43.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems
AU - Rao, Aakarsh
AU - Carreon, Nadir
AU - Lysecky, Roman L
AU - Rozenblit, Jerzy W
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Medical devices are complex cyber-physical systems incorporating emergent hardware and software components. However, this complexity leads to a wide attack surface posing security risks and vulnerabilities. Mitigation and management of such risks during premarket design and postmarket deployment are required. Dynamically mitigating threat potential in the presence of unknown vulnerabilities requires an adaptive risk-based scheme to assess the system's state, a secure system architecture that can isolate hardware and software components, and design methods that can adaptively adjust the system's topology based on risk changes. The essential complementary aspects during deployment are detecting, characterizing, and quantifying security threats. This article presents a dynamic risk management and mitigation approach based on probabilistic threat estimation. A smart-connected-pacemaker case study illustrates the approach. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
AB - Medical devices are complex cyber-physical systems incorporating emergent hardware and software components. However, this complexity leads to a wide attack surface posing security risks and vulnerabilities. Mitigation and management of such risks during premarket design and postmarket deployment are required. Dynamically mitigating threat potential in the presence of unknown vulnerabilities requires an adaptive risk-based scheme to assess the system's state, a secure system architecture that can isolate hardware and software components, and design methods that can adaptively adjust the system's topology based on risk changes. The essential complementary aspects during deployment are detecting, characterizing, and quantifying security threats. This article presents a dynamic risk management and mitigation approach based on probabilistic threat estimation. A smart-connected-pacemaker case study illustrates the approach. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
KW - medical-device security
KW - risk assessment and management
KW - software development
KW - software engineering
KW - threat estimation
UR - http://www.scopus.com/inward/record.url?scp=85040312293&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040312293&partnerID=8YFLogxK
U2 - 10.1109/MS.2017.4541031
DO - 10.1109/MS.2017.4541031
M3 - Article
AN - SCOPUS:85040312293
VL - 35
SP - 38
EP - 43
JO - IEEE Software
JF - IEEE Software
SN - 0740-7459
IS - 1
M1 - 8239935
ER -