Securing Additive Manufacturing with Blockchains and Distributed Physically Unclonable Functions

Autor: Bertrand Cambou, Michael Gowanlock, Julie Heynssens, Saloni Jain, Christopher Philabaum, Duane Booher, Ian Burke, Jack Garrard, Donald Telesca, Laurent Njilla
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Cryptography, Vol 4, Iss 2, p 17 (2020)
Druh dokumentu: article
ISSN: 2410-387X
DOI: 10.3390/cryptography4020017
Popis: Blockchain technology is a game-changing, enhancing security for the supply chain of smart additive manufacturing. Blockchain enables the tracking and recording of the history of each transaction in a ledger stored in the cloud that cannot be altered, and when blockchain is combined with digital signatures, it verifies the identity of the participants with its non-repudiation capabilities. One of the weaknesses of blockchain is the difficulty of preventing malicious participants from gaining access to public–private key pairs. Groups of opponents often interact freely with the network, and this is a security concern when cloud-based methods manage the key pairs. Therefore, we are proposing end-to-end security schemes by both inserting tamper-resistant devices in the hardware of the peripheral devices and using ternary cryptography. The tamper-resistant devices, which are designed with nanomaterials, act as Physical Unclonable Functions to generate secret cryptographic keys. One-time use public–private key pairs are generated for each transaction. In addition, the cryptographic scheme incorporates a third logic state to mitigate man-in-the-middle attacks. The generation of these public–private key pairs is compatible with post quantum cryptography. The third scheme we are proposing is the use of noise injection techniques used with high-performance computing to increase the security of the system. We present prototypes to demonstrate the feasibility of these schemes and to quantify the relevant parameters. We conclude by presenting the value of blockchains to secure the logistics of additive manufacturing operations.
Databáze: Directory of Open Access Journals