A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems. (July 2020)
- Record Type:
- Journal Article
- Title:
- A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems. (July 2020)
- Main Title:
- A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems
- Authors:
- Brandman, Josh
Sturm, Logan
White, Jules
Williams, Chris - Abstract:
- Highlights: Secure transfer of quality control data with part file. Air-gapped side-channel measurement system extracts quality data from print. Physical hash detects toolpath and process parameter changes in additively manufactured parts. Abstract: Cyber-physical security is a major concern in the modern environment of digital manufacturing, wherein a cyber-attack has the potential to result in the production of defective parts, theft of IP, or damage to infrastructure or the operator have become a real threat that have the potential to create bad parts. Current cyber only solutions are insufficient due to the nature of manufacturing environments where it may not be feasible or even possible to upgrade physical equipment to the most current cyber security standards, necessitating an approach that addresses both the cyber and the physical components. This paper proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system becomes compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash ensures protection of the intellectual property (IP) associated with both process and toolpath parameters while also enabling in situ quality assurance. In this paper, the physical hash takesHighlights: Secure transfer of quality control data with part file. Air-gapped side-channel measurement system extracts quality data from print. Physical hash detects toolpath and process parameter changes in additively manufactured parts. Abstract: Cyber-physical security is a major concern in the modern environment of digital manufacturing, wherein a cyber-attack has the potential to result in the production of defective parts, theft of IP, or damage to infrastructure or the operator have become a real threat that have the potential to create bad parts. Current cyber only solutions are insufficient due to the nature of manufacturing environments where it may not be feasible or even possible to upgrade physical equipment to the most current cyber security standards, necessitating an approach that addresses both the cyber and the physical components. This paper proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system becomes compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash ensures protection of the intellectual property (IP) associated with both process and toolpath parameters while also enabling in situ quality assurance. In this paper, the physical hash takes the form of a QR code that contains a hash string of the nominal process parameters and toolpath. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in situ, the measurement system can detect in real-time if the part being manufactured matches the designer's specification. In this paper, the overall concept and underlying algorithm of the physical hash is presented. A proof-of-concept validation is realized on a material extrusion AM machine, to demonstrate the ability of a physical hash and in situ monitoring to detect the existence (and absence) of malicious attacks on the STL file, the printing process parameters, and the printing toolpath. … (more)
- Is Part Of:
- Journal of manufacturing systems. Volume 56(2020)
- Journal:
- Journal of manufacturing systems
- Issue:
- Volume 56(2020)
- Issue Display:
- Volume 56, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 56
- Issue:
- 2020
- Issue Sort Value:
- 2020-0056-2020-0000
- Page Start:
- 202
- Page End:
- 212
- Publication Date:
- 2020-07
- Subjects:
- Cyber-physical security -- Additive manufacturing -- 3D printing -- Physical hash -- In situ monitoring -- Side-channel measurement
Manufacturing processes -- Periodicals
Production engineering -- Data processing -- Periodicals
Robots, Industrial -- Periodicals
Production, Technique de la -- Informatique -- Périodiques
Robots industriels -- Périodiques
Electronic journals
670.42 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02786125 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jmsy.2020.05.014 ↗
- Languages:
- English
- ISSNs:
- 0278-6125
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5011.650000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14019.xml