10.25394/PGS.11879106.v1
Matthew Lee Scott
Matthew Lee
Scott
Preventing Intellectual Property Theft in Additive Manufacturing
Purdue University Graduate School
2020
blockchain
intellectual property management
additive manufacturing
attack vectors
Cyber security
Computer Software
Computer System Architecture
Conceptual Modelling
Data Encryption
Distributed Computing
Networking and Communications
Computer Communications Networks
Data Communications
Input, Output and Data Devices
Technology not elsewhere classified
2020-02-24 13:05:07
Educational resource
https://hammer.purdue.edu/articles/educational_resource/Preventing_Intellectual_Property_Theft_in_Additive_Manufacturing/11879106
Advanced manufacturing machines, especially for additive manufacturing, are taking advantage of the latest technologies for maximum optimization and precision. Efforts to communicate the complex information, however, can leave systems vulnerable to various attacks both from inside and outside a company’s network. Intellectual property theft attack vectors must be fully understood and accounted for within the information security framework. Software solutions, such as blockchain, will enable full transactional accountability needed to ensure theft cannot occur throughout the manufacturing lifecycle. The resultant research and expert interviews provide a thorough analysis of the elements at risk for which blockchain opportunities will mitigate.