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.

Schemes generating cryptographic keys from arrays of pre-formed Resistive Random Access (ReRAM) cells, called memristors, can also be used for the design of fast true random number generators (TRNG’s) of exceptional quality, while consuming low levels of electric power. Natural randomness is formed in the large stochastic cell-to-cell variations in resistance values at low injected currents in the pre-formed range. The proposed TRNG scheme can be designed with three interconnected blocks: (i) a pseudo-random number generator that acts as an extended output function to generate a stream of addresses pointing randomly at the array of ReRAM cells; (ii) a method to read the resistance values of these cells with a low injected current, and to convert the values into a stream of random bits; and, if needed, (iii) a method to further enhance the randomness of this stream such as mathematical, Boolean, and cryptographic algorithms. The natural stochastic properties of the ReRAM cells in the pre-forming range, at low currents, have been analyzed and demonstrated by measuring a statistically significant number of cells. Various implementations of the TRNGs with ReRAM arrays are presented in this paper.

Physical unclonable functions, embedded in terminal devices, can be used as part of the recovery process of session keys that protect digital files. Such an approach is only valuable when the physical element offers sufficient tamper resistance. Otherwise, error correcting codes should be able to handle any variations arising from aging, and environmentally induced drifts of the terminal devices. The ternary cryptographic protocols presented in this paper, leverage the physical properties of resistive random-access memories operating at extremely low power in the pre-forming range to create an additional level of security, while masking the most unstable cells during key generation cycles. The objective is to reach bit error rates below the 10⁻³ range from elements subjected to drifts and environmental effects. We propose replacing the error correcting codes with light search engines, that use ciphertexts as helper data to reduce information leakage. The tamper-resistant schemes discussed in the paper include: (i) a cell-pairing differential method to hide the physical parameters; (ii) an attack detection system and a low power self-destruct mode; (iii) a multi-factor authentication, information control, and a one-time read-only function. In the experimental section, we describe how prototypes were fabricated to test and quantify the performance of the suggested methods, using static random access memory devices as the benchmark.

Cryptographic protocols are widely deployed to enhance the security of sensitive data shared across autonomous networks. Privacy and security issues are exacerbated due to increased vulnerability of the cryptographic key to various types of attack. It is extremely challenging to distribute cryptographic keys in contested areas on a real-time basis, therefore several protocols have been developed that use the fingerprints of electronic devices embedded in cyber physical systems for one-time use key generation. Various autonomous systems, including vehicles, robots, and industrial machines may be protected by these fingerprints, thus allowing the use of onetime encryption keys, thereby reducing the cybersecurity attack surface. To mitigate certain attacks and enhance security we propose methods to inject random noise in these keys, as well as the associated key recovery schemes. The benefit of noise injection is the ability to incrementally confuse the hacker while adding an extra layer of authenticity. The random percentage of noise injected in the key can only be identified and verified by an authorized party. An unexpected increase or decrease in the percentage of noise notifies the server that the autonomous system is potentially under attack. Experimentally, we demonstrate how noise levels up to 30% of the cryptographic keys can be injected, and how the temperature can alter the percentage of noise. We also quantify methods to increase the errors due to the instability of the fingerprints. Additionally, we review different strategies of noise injection and how we may leverage the injected noise for stronger authentication.