Randomly Encoding Functions: A New Cryptographic Paradigm

Vipul Goyal, Abhishek Jain, Venkata Koppula +1 more

Jeong Jin Kim, Min Seong Kim, Gil Ju Lee

Optical physical unclonable functions (PUFs) have emerged as a promising cryptographic primitive for next-generation security. However, to harmonize with various modern networks, conventional optical PUF is inadequate due to a rigid key space with a fixed specification. This study implements hierarchically controllable randomness sources for multi-level key generation, exploiting speckle characteristics. By adjusting illumination diameter, the speckle size can be modulated, allowing the extraction of three-level keys with various lengths: 64, 256, and 1,024 bits. Performance evaluation reveals that all levels are superb in uniformity, uniqueness, reproducibility, and randomness. Moreover, it is proposed two feasible applications. The first is a hierarchical authentication architecture that spans from Internet of Things (IoT) devices to sensitive information, balancing security and resources. The second is a multi-stage image encryption algorithm, exhibiting holocryptic performance superior to conventional XOR-based encryption. This versatile platform sets a new paradigm for optical PUF, establishing a foundation for robust and expandable next-generation security.

Edwin Cartlidge

A new scheme that encodes and decodes messages using the random arrival of cosmic-ray muons could be more secure than other cryptographic systems. Edwin Cartlidge reports.

Marcin Płodzień

Training the circuit of a quantum generative model is hampered by barren plateaus, where gradients vanish exponentially with the number of qubits. In the present work we propose a generative protocol based on the paradigm of quantum extreme learning machines, in which the circuit is never trained. A random latent vector is encoded into a quantum state, evolved with a fixed unitary and measured, and only a linear output layer is trained. The encoding of the latent variable determines the functions available to the model, while the unitary decides which combinations of them are seen by the trained layer. With the help of Pauli propagation we show that for a Clifford unitary each feature is a single product of sines and cosines of the encoded angles, so that a Clifford circuit, even a strongly entangling one, does not create new functions. Doping the circuit with $T$ gates mixes these products and changes the nonstabilizerness of the state, but the space of functions remains the one fixed by the encoding. For brickworks of Haar-random two-qubit gates the features are no longer single products, and their variation with the latent variable decreases with the depth of the circuit. For the proposed encoding and for one- and two-dimensional distributions, generated both from expectation values and from single measurements, neither the entanglement produced by a Clifford reservoir nor the additional nonstabilizerness of Haar-random brickworks systematically improves the generator, and a reservoir with no gates at all is competitive with entangling circuits.

Hao Chen, Ronald Cramer, Shafi Goldwasser +2 more

Bartosz Przydatek