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.