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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.

Networks of low-power Internet of Things do not have always access to enough computing power to support mainstream cryptographic schemes; such schemes also consume computing power that can be exposed to side channel attacks. This article describes a method, that we call “cryptography with analog scheme using memristors,” leveraging the physical properties of memristors, which are active elements suitable for the design of components such as artificial neurons. The proposed devices encrypt messages by segmenting them into blocks of bits, each modulating the injected currents into randomly selected memristor cells, resulting into sets of resistance values turned into cipher texts. Through hash-protected handshakes, identical addresses are independently generated by both communicating devices, to concurrently point at the same set of cells in the arrays, and their images. These block ciphers, for example, 1 KB long, can only be decrypted with the same memristor array driven by analog circuitry or its image, rather than digital key-based schemes. The proposed methods generate cipher text, and decrypt them, with approximately one femto joule per bit, which is below observable level through differential power analysis. The article explains how the use of different cells for each message to encrypt, driven under different conditions, has the potential to mitigate mainstream attacks. It provides a detailed characterization of memristors to evaluate the feasibility of the approach and discusses some hardware and architectures to implement the scheme.

Some of the main challenges towards utilizing conventional cryptographic techniques in Internet of Things (IoT) include the need for generating secret keys for such a large-scale network, distributing the generated keys to all the devices, key storage as well as the vulnerability to security attacks when an adversary gets physical access to the devices. In this paper, a novel secret key generation method is proposed for IoTs that utilize the intrinsic randomness embedded in the devices' memories introduced in the manufacturing process. A fuzzy extractor structure using serially concatenated BCH-Polar codes is proposed to generate reproducible keys from a ReRAM-based ternary-state Physical Unclonable Functions (PUFs) for device authentication and secret key generation. The main concern in deploying PUF-based key generation methods is the leakage of information about the secret keys from the publicly available helper data. The fuzzy extractor proposed in this paper ensures much less mutual information between the generated keys and the helper data. The experimental results show that our proposed scheme is capable of generating notably stronger keys compared to existing techniques, while utilizing a significantly lower number of helper data bits. The failure probability when a low complex Successive Cancellation decoder is implemented in the proposed fuzzy extractor structure is 10 −8 which was further increased to 10 −10 when a complex iterative belief propagation decoder was used. 1

Lattice and code cryptography can replace existing schemes such as elliptic curve cryptography because of their resistance to quantum computers. In support of public key infrastructures, the distribution, validation and storage of the cryptographic keys is then more complex for handling longer keys. This paper describes practical ways to generate keys from physical unclonable functions, for both lattice and code-based cryptography. Handshakes between client devices containing the physical unclonable functions (PUFs) and a server are used to select sets of addressable positions in the PUFs, from which streams of bits called seeds are generated on demand. The public and private cryptographic key pairs are computed from these seeds together with additional streams of random numbers. The method allows the server to independently validate the public key generated by the PUF, and act as a certificate authority in the network. Technologies such as high performance computing, and graphic processing units can further enhance security by preventing attackers from making this independent validation when only equipped with less powerful computers.

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