Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems

Aakarsh Rao; Nadir Carreon Rascon; Roman Lysecky; J. W. Rozenblit

doi:10.1109/MS.2018.110165557

Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems

Aakarsh Rao
, Nadir Carreon Rascon
, Roman Lysecky
, J. W. Rozenblit

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Medical devices are complex cyber-physical systems exposed to numerous security risks and vulnerabilities. This article presents a dynamic risk management and automated threat mitigation approach based on a probabilistic threat estimation framework. A smart-connected-pacemaker case study illustrates the approach.

Original language	English (US)
Pages (from-to)	38-43
Number of pages	6
Journal	IEEE Software
Volume	35
Issue number	1
DOIs	https://doi.org/10.1109/MS.2018.110165557
State	Published - Jan 2018

ASJC Scopus subject areas

Software

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title = "Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems",

abstract = "Medical devices are complex cyber-physical systems exposed to numerous security risks and vulnerabilities. This article presents a dynamic risk management and automated threat mitigation approach based on a probabilistic threat estimation framework. A smart-connected-pacemaker case study illustrates the approach.",

author = "Aakarsh Rao and \{Carreon Rascon\}, Nadir and Roman Lysecky and Rozenblit, \{J. W.\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",

year = "2018",

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doi = "10.1109/MS.2018.110165557",

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T1 - Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems

AU - Rao, Aakarsh

AU - Carreon Rascon, Nadir

AU - Lysecky, Roman

AU - Rozenblit, J. W.

PY - 2018/1

Y1 - 2018/1

N2 - Medical devices are complex cyber-physical systems exposed to numerous security risks and vulnerabilities. This article presents a dynamic risk management and automated threat mitigation approach based on a probabilistic threat estimation framework. A smart-connected-pacemaker case study illustrates the approach.

AB - Medical devices are complex cyber-physical systems exposed to numerous security risks and vulnerabilities. This article presents a dynamic risk management and automated threat mitigation approach based on a probabilistic threat estimation framework. A smart-connected-pacemaker case study illustrates the approach.

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U2 - 10.1109/MS.2018.110165557

DO - 10.1109/MS.2018.110165557

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SP - 38

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JO - IEEE Software

JF - IEEE Software

IS - 1

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Probabilistic Threat Detection for Risk Management in Cyber-physical Medical Systems

Abstract

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