Demonstrating Danger Theory based threat detection for robotic manufacture protection

V. Degeler; Richard French; Kevin Jones

doi:10.1109/IntelliSys.2015.7361156

Demonstrating Danger Theory based threat detection for robotic manufacture protection

V. Degeler, Richard French, Kevin Jones

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

The aid of automated guided vehicles (AGV) is indispensable for complex manufacturing processes. However, a cyber attack on an AGV or an AGV control centre can easily lead o considerable direct physical damage and further indirect costs due to disruption of manufacturing process. Previous incidents show that most damage comes from previously unseen threats, hose that cannot be prevented by detecting known attack signatures. In this demo, we show an approach to protect industrial process of robotic manufacture facilities from cyber attacks based on Artificial Immune Systems paradigm using Danger Theory.

Original language	English
Title of host publication	IntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference
Publisher	IEEE
Pages	283-284
ISBN (Print)	978-1-4673-7606-8
DOIs	https://doi.org/10.1109/IntelliSys.2015.7361156
Publication status	Published - 2015
Externally published	Yes
Event	SAI Intelligent Systems Conference 2015 - London, United Kingdom Duration: 10-Nov-2015 → 11-Nov-2015

Conference

Conference	SAI Intelligent Systems Conference 2015
Country/Territory	United Kingdom
City	London
Period	10/11/2015 → 11/11/2015

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10.1109/IntelliSys.2015.7361156

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title = "Demonstrating Danger Theory based threat detection for robotic manufacture protection",

abstract = "The aid of automated guided vehicles (AGV) is indispensable for complex manufacturing processes. However, a cyber attack on an AGV or an AGV control centre can easily lead o considerable direct physical damage and further indirect costs due to disruption of manufacturing process. Previous incidents show that most damage comes from previously unseen threats, hose that cannot be prevented by detecting known attack signatures. In this demo, we show an approach to protect industrial process of robotic manufacture facilities from cyber attacks based on Artificial Immune Systems paradigm using Danger Theory.",

author = "V. Degeler and Richard French and Kevin Jones",

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doi = "10.1109/IntelliSys.2015.7361156",

language = "English",

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publisher = "IEEE",

note = "SAI Intelligent Systems Conference 2015 ; Conference date: 10-11-2015 Through 11-11-2015",

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AU - French, Richard

AU - Jones, Kevin

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AB - The aid of automated guided vehicles (AGV) is indispensable for complex manufacturing processes. However, a cyber attack on an AGV or an AGV control centre can easily lead o considerable direct physical damage and further indirect costs due to disruption of manufacturing process. Previous incidents show that most damage comes from previously unseen threats, hose that cannot be prevented by detecting known attack signatures. In this demo, we show an approach to protect industrial process of robotic manufacture facilities from cyber attacks based on Artificial Immune Systems paradigm using Danger Theory.

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U2 - 10.1109/IntelliSys.2015.7361156

DO - 10.1109/IntelliSys.2015.7361156

M3 - Conference contribution

SN - 978-1-4673-7606-8

SP - 283

EP - 284

BT - IntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference

PB - IEEE

T2 - SAI Intelligent Systems Conference 2015

Y2 - 10 November 2015 through 11 November 2015

ER -

Demonstrating Danger Theory based threat detection for robotic manufacture protection

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