Intrusion detection system for cyber-manufacturing system

Mingtao Wu, Young Bai Moon

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Cyber-manufacturing system (CMS) offers a blueprint for future manufacturing systems in which physical components are fully integrated with computational processes in a connected environment. Similar concepts and visions have been developed to different extents and under different names-"Industrie 4.0" in Germany, "Monozukuri" in Japan, "Factories of the Future" in the EU, and "Industrial Internet" by GE. However, CMS opens a door for cyber-physical attacks on manufacturing systems. Current computer and information security methods-firewalls and intrusion detection system (IDS), etc.-cannot detect the malicious attacks in CMS with adequate response time and accuracy. Realization of the promising CMS depends on addressing cyber-physical security issues effectively. These attacks can cause physical damages to physical components-machines, equipment, parts, assemblies, products-through over-wearing, breakage, scrap parts or other changes that designers did not intend. This research proposes a conceptual design of a system to detect cyber-physical intrusions in CMS. To accomplish this objective, physical data from the manufacturing process level and production system level are integrated with cyber data from network-based and host-based IDSs. The correlations between the cyber and physical data are analyzed. Machine learning methods are adapted to detect the intrusions. Three-dimensional (3D) printing and computer numerical control (CNC) milling process are used as examples of manufacturing processes for detecting cyber-physical attacks. A cyber-physical attack scenario is presented with preliminary results to illustrate how the system can be used.

Original languageEnglish (US)
Article number031007
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Volume141
Issue number3
DOIs
StatePublished - Mar 1 2019

Fingerprint

Intrusion detection
Security of data
Blueprints
Machine components
Conceptual design
Industrial plants
Learning systems
Printing
Internet

Keywords

  • Cyber-manufacturing system
  • Cyber-physical attack
  • Intrusion detection
  • Security

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

Intrusion detection system for cyber-manufacturing system. / Wu, Mingtao; Moon, Young Bai.

In: Journal of Manufacturing Science and Engineering, Transactions of the ASME, Vol. 141, No. 3, 031007, 01.03.2019.

Research output: Contribution to journalArticle

@article{2c9e7494f473479995d01344127bee4f,
title = "Intrusion detection system for cyber-manufacturing system",
abstract = "Cyber-manufacturing system (CMS) offers a blueprint for future manufacturing systems in which physical components are fully integrated with computational processes in a connected environment. Similar concepts and visions have been developed to different extents and under different names-{"}Industrie 4.0{"} in Germany, {"}Monozukuri{"} in Japan, {"}Factories of the Future{"} in the EU, and {"}Industrial Internet{"} by GE. However, CMS opens a door for cyber-physical attacks on manufacturing systems. Current computer and information security methods-firewalls and intrusion detection system (IDS), etc.-cannot detect the malicious attacks in CMS with adequate response time and accuracy. Realization of the promising CMS depends on addressing cyber-physical security issues effectively. These attacks can cause physical damages to physical components-machines, equipment, parts, assemblies, products-through over-wearing, breakage, scrap parts or other changes that designers did not intend. This research proposes a conceptual design of a system to detect cyber-physical intrusions in CMS. To accomplish this objective, physical data from the manufacturing process level and production system level are integrated with cyber data from network-based and host-based IDSs. The correlations between the cyber and physical data are analyzed. Machine learning methods are adapted to detect the intrusions. Three-dimensional (3D) printing and computer numerical control (CNC) milling process are used as examples of manufacturing processes for detecting cyber-physical attacks. A cyber-physical attack scenario is presented with preliminary results to illustrate how the system can be used.",
keywords = "Cyber-manufacturing system, Cyber-physical attack, Intrusion detection, Security",
author = "Mingtao Wu and Moon, {Young Bai}",
year = "2019",
month = "3",
day = "1",
doi = "10.1115/1.4042053",
language = "English (US)",
volume = "141",
journal = "Journal of Manufacturing Science and Engineering, Transactions of the ASME",
issn = "1087-1357",
publisher = "American Society of Mechanical Engineers(ASME)",
number = "3",

}

TY - JOUR

T1 - Intrusion detection system for cyber-manufacturing system

AU - Wu, Mingtao

AU - Moon, Young Bai

PY - 2019/3/1

Y1 - 2019/3/1

N2 - Cyber-manufacturing system (CMS) offers a blueprint for future manufacturing systems in which physical components are fully integrated with computational processes in a connected environment. Similar concepts and visions have been developed to different extents and under different names-"Industrie 4.0" in Germany, "Monozukuri" in Japan, "Factories of the Future" in the EU, and "Industrial Internet" by GE. However, CMS opens a door for cyber-physical attacks on manufacturing systems. Current computer and information security methods-firewalls and intrusion detection system (IDS), etc.-cannot detect the malicious attacks in CMS with adequate response time and accuracy. Realization of the promising CMS depends on addressing cyber-physical security issues effectively. These attacks can cause physical damages to physical components-machines, equipment, parts, assemblies, products-through over-wearing, breakage, scrap parts or other changes that designers did not intend. This research proposes a conceptual design of a system to detect cyber-physical intrusions in CMS. To accomplish this objective, physical data from the manufacturing process level and production system level are integrated with cyber data from network-based and host-based IDSs. The correlations between the cyber and physical data are analyzed. Machine learning methods are adapted to detect the intrusions. Three-dimensional (3D) printing and computer numerical control (CNC) milling process are used as examples of manufacturing processes for detecting cyber-physical attacks. A cyber-physical attack scenario is presented with preliminary results to illustrate how the system can be used.

AB - Cyber-manufacturing system (CMS) offers a blueprint for future manufacturing systems in which physical components are fully integrated with computational processes in a connected environment. Similar concepts and visions have been developed to different extents and under different names-"Industrie 4.0" in Germany, "Monozukuri" in Japan, "Factories of the Future" in the EU, and "Industrial Internet" by GE. However, CMS opens a door for cyber-physical attacks on manufacturing systems. Current computer and information security methods-firewalls and intrusion detection system (IDS), etc.-cannot detect the malicious attacks in CMS with adequate response time and accuracy. Realization of the promising CMS depends on addressing cyber-physical security issues effectively. These attacks can cause physical damages to physical components-machines, equipment, parts, assemblies, products-through over-wearing, breakage, scrap parts or other changes that designers did not intend. This research proposes a conceptual design of a system to detect cyber-physical intrusions in CMS. To accomplish this objective, physical data from the manufacturing process level and production system level are integrated with cyber data from network-based and host-based IDSs. The correlations between the cyber and physical data are analyzed. Machine learning methods are adapted to detect the intrusions. Three-dimensional (3D) printing and computer numerical control (CNC) milling process are used as examples of manufacturing processes for detecting cyber-physical attacks. A cyber-physical attack scenario is presented with preliminary results to illustrate how the system can be used.

KW - Cyber-manufacturing system

KW - Cyber-physical attack

KW - Intrusion detection

KW - Security

UR - http://www.scopus.com/inward/record.url?scp=85060515147&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85060515147&partnerID=8YFLogxK

U2 - 10.1115/1.4042053

DO - 10.1115/1.4042053

M3 - Article

AN - SCOPUS:85060515147

VL - 141

JO - Journal of Manufacturing Science and Engineering, Transactions of the ASME

JF - Journal of Manufacturing Science and Engineering, Transactions of the ASME

SN - 1087-1357

IS - 3

M1 - 031007

ER -