Imperial College London
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ProfessorMichaelHuth

Faculty of Engineering, Department of Computing

Head of the Department of Computing
 
 
 
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Contact

 

m.huth Website

 
 
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Location

 

Huxley 566Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Radanliev:2018:10.1016/j.compind.2018.08.002,
author = {Radanliev, P and De, Roure DC and Nicolescu, R and Huth, M and Montalvo, RM and Cannady, S and Burnap, P},
doi = {10.1016/j.compind.2018.08.002},
journal = {Computers in Industry},
pages = {14--22},
title = {Future developments in cyber risk assessment for the internet of things},
url = {http://dx.doi.org/10.1016/j.compind.2018.08.002},
volume = {102},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This article is focused on the economic impact assessment of Internet of Things (IoT) and its associated cyber risks vectors and vertices – a reinterpretation of IoT verticals. We adapt to IoT both the Cyber Value at Risk model, a well-established model for measuring the maximum possible loss over a given time period, and the MicroMort model, a widely used model for predicting uncertainty through units of mortality risk. The resulting new IoT MicroMort for calculating IoT risk is tested and validated with real data from the BullGuard's IoT Scanner (over 310,000 scans) and the Garner report on IoT connected devices. Two calculations are developed, the current state of IoT cyber risk and the future forecasts of IoT cyber risk. Our work therefore advances the efforts of integrating cyber risk impact assessments and offer a better understanding of economic impact assessment for IoT cyber risk.
AU  - Radanliev,P
AU  - De,Roure DC
AU  - Nicolescu,R
AU  - Huth,M
AU  - Montalvo,RM
AU  - Cannady,S
AU  - Burnap,P
DO  - 10.1016/j.compind.2018.08.002
EP  - 22
PY  - 2018///
SN  - 0166-3615
SP  - 14
TI  - Future developments in cyber risk assessment for the internet of things
T2  - Computers in Industry
UR  - http://dx.doi.org/10.1016/j.compind.2018.08.002
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000448097200002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/70852
VL  - 102
ER  -
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