Developments in digital technology and manufacturing processes have expanded the horizon of designer innovation in creating products. In addition to this, real-time collaborative platforms help designers shorten the product development cycle by enabling collaborations with domain experts from concept generation to product realization and after-market. These collaborations are extending beyond enterprise and national boundaries, contributing to a growing concern among designers regarding the security of their sensitive information such as intellectual property (IP) and trade secrets. The source of such sensitive information leaks could be external (e.g., hacker) or internal (e.g., disgruntled employee) to the collaboration. From a designer's perspective, this fear can inhibit participation in a collaboration even though it might result in better products or services. In this paper, we aim to contextualize this evolving security space by discussing various security practices in digital domains, such as encryption and secret sharing, as well as manufacturing domains, such as physically unclonable function (PUF) and physical part watermarking for anticounterfeiting and tamper evidence purposes. Further, we classify these practices with respect to their performance against different adversarial models for different stages in product development. Such a classification can help designers to make informed decisions regarding security practices during the product realization process.
Skip Nav Destination
Article navigation
December 2018
Review Articles
Security in Cyber-Enabled Design and Manufacturing: A Survey
Siva Chaitanya Chaduvula,
Siva Chaitanya Chaduvula
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: schaduvu@purdue.edu
Purdue University,
West Lafayette, IN 47907
e-mail: schaduvu@purdue.edu
Search for other works by this author on:
Adam Dachowicz,
Adam Dachowicz
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: adachowi@purdue.edu
Purdue University,
West Lafayette, IN 47907
e-mail: adachowi@purdue.edu
Search for other works by this author on:
Mikhail J. Atallah,
Mikhail J. Atallah
Department of Computer Science,
Purdue University,
West Lafayette, IN 47907
Purdue University,
West Lafayette, IN 47907
Search for other works by this author on:
Jitesh H. Panchal
Jitesh H. Panchal
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
Purdue University,
West Lafayette, IN 47907
Search for other works by this author on:
Siva Chaitanya Chaduvula
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: schaduvu@purdue.edu
Purdue University,
West Lafayette, IN 47907
e-mail: schaduvu@purdue.edu
Adam Dachowicz
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: adachowi@purdue.edu
Purdue University,
West Lafayette, IN 47907
e-mail: adachowi@purdue.edu
Mikhail J. Atallah
Department of Computer Science,
Purdue University,
West Lafayette, IN 47907
Purdue University,
West Lafayette, IN 47907
Jitesh H. Panchal
School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
Purdue University,
West Lafayette, IN 47907
Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received February 9, 2018; final manuscript received May 8, 2018; published online July 5, 2018. Assoc. Editor: Mahesh Mani.
J. Comput. Inf. Sci. Eng. Dec 2018, 18(4): 040802 (15 pages)
Published Online: July 5, 2018
Article history
Received:
February 9, 2018
Revised:
May 8, 2018
Citation
Chaduvula, S. C., Dachowicz, A., Atallah, M. J., and Panchal, J. H. (July 5, 2018). "Security in Cyber-Enabled Design and Manufacturing: A Survey." ASME. J. Comput. Inf. Sci. Eng. December 2018; 18(4): 040802. https://doi.org/10.1115/1.4040341
Download citation file:
Get Email Alerts
Manufacturing Feature Recognition with a Sparse Voxel-based Convolutional Neural Network
J. Comput. Inf. Sci. Eng
Ontology-Guided Data Sharing and Federated Quality Control With Differential Privacy in Additive Manufacturing
J. Comput. Inf. Sci. Eng (January 2025)
Related Articles
An Internet of Things-Based Monitoring System for Shop-Floor Control
J. Comput. Inf. Sci. Eng (June,2018)
Extraction and Analysis of Spatial Correlation Micrograph Features for Traceability in Manufacturing
J. Comput. Inf. Sci. Eng (October,2020)
Application of Polynomial Chaos Expansion to Tolerance Analysis and Synthesis in Compliant Assemblies Subject to Loading
J. Mech. Des (March,2015)
Manufacturing Feature Recognition with a Sparse Voxel-based Convolutional Neural Network
J. Comput. Inf. Sci. Eng (January,0001)
Related Proceedings Papers
Related Chapters
CAD/CAE Simulation Optimization
Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications
Computer Aided Design of Tools, Dies, and Moulds (TDMs)
Computer Aided Design and Manufacturing
Managing Energy Resources from within the Corporate Information Technology System
Industrial Energy Systems