Akash Tiwari, Eduardo Jose Villasenor, Nikhil Gupta, N. Reddy, R. Karri, S. Bukkapatnam
{"title":"Protection against Counterfeiting Attacks in 3D Printing by Streaming Signature-embedded Manufacturing Process Instructions","authors":"Akash Tiwari, Eduardo Jose Villasenor, Nikhil Gupta, N. Reddy, R. Karri, S. Bukkapatnam","doi":"10.1145/3462223.3485620","DOIUrl":"https://doi.org/10.1145/3462223.3485620","url":null,"abstract":"The emerging Manufacturing-as-a-Service (MaaS) paradigm democratizes manufacturing by connecting people and businesses with manufacturing requests to those with manufacturing resources, via a digital thread. However, the digital thread can be vulnerable to attacks such as counterfeiting, IP theft and sabotage. An approach based on embedding custom anti-counterfeiting signatures in the design files, on-the-fly, is presented to protect against counterfeiting attacks. An experimental study of the effect of geometric and dimensional variations of the signatures in printed components, as well as the effect of the variations on the read rates of the codes are reported. We conduct experiments using a polyjet printer with veroclear material to study the positional and dimensional variations introduced in the embedded signature and the resulting effect on the readability of the design. The results suggest that signatures with spherical units of size φ0.25 mm embedded within 20 mm cubic components can be printed with location precision of ~5% (about 0.1 mm), and dimensional deviation of the order of 0.01 mm. A statistical model is developed to show that these variations pose minimum interference on the readability of the signatures. Embedding of randomized signatures offers security by serving as anti-counterfeit marks in the final part, and makes it harder to reverse engineer and produce counterfeited parts.","PeriodicalId":113006,"journal":{"name":"Proceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129903548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Felix Engelmann, J. Speichert, R. God, F. Kargl, Christoph Bösch
{"title":"Confidential Token-Based License Management","authors":"Felix Engelmann, J. Speichert, R. God, F. Kargl, Christoph Bösch","doi":"10.1145/3462223.3485619","DOIUrl":"https://doi.org/10.1145/3462223.3485619","url":null,"abstract":"In a global economy with many competitive participants, licensing and tracking of 3D printed parts is desirable if not mandatory for many use-cases. We investigate a blockchain-based approach, as blockchains provide many attractive features, like decentralized architecture and high security assurances. An often neglected aspect of the product life-cycle management is the confidentiality of transactions to hide valuable business information from competitors. To solve the combined problem of trust and confidentiality, we present a confidential licensing and tracking system which works on any publicly verifiable, token-based blockchain that supports tokens of different types representing licenses or attributes of parts. Together with the secure integration of a unique eID in each part, our system provides an efficient, immutable and authenticated transaction log scalable to thousands of transactions per second. With our confidential Token-Based License Management system (cTLM), large industries such as automotive or aviation can license and trace all parts confidentially.","PeriodicalId":113006,"journal":{"name":"Proceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security","volume":"927 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116090746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}