Scientists from the Institute of Electronic Structures and Lasers, the Hellas Research and Technology Foundation and the University of Crete have developed a new optical system that uses holograms to encrypt data, creating a level of encryption that is impenetrable to conventional techniques, as the need for digital security grows. The development could protect sensitive data, potentially opening the door to more secure communication channels. The study was published in the journal Optica.
From rapidly evolving digital currencies to governance, healthcare, communications and social media, the demand for robust protection systems to combat digital fraud is ever-increasing. Our new system achieves an exceptional level of encryption by using a neural network to generate a decryption key that can only be created by the owner of the encryption system .
Stelios Tzortzakis, Research Team Leader, University of Crete
The new system uses neural networks to reconstruct entangled data stored as holograms. The researchers showed that trained neural networks can successfully decode complex spatial information in cluttered images.
Our study provides a solid foundation for many applications, especially for cryptography and secure wireless optical communication, and paves the way for next-generation telecommunications technologies. The method we developed is highly reliable even in harsh and unpredictable conditions, overcoming real-world challenges such as harsh weather that often limit the performance of optical systems in free space .
Stelios Tzortzakis, Research Team Leader, University of Crete
Dimmed light for safety
The researchers created the new system after realizing that the laser beam encoded in the hologram is completely and randomly entangled, and the shape of the original beam cannot be identified or reconstructed through physical analysis or calculations. They realized that this was the best way to securely encrypt data.
The challenge was how to decode the information. We came up with the idea of training neural networks to recognize the incredibly fine details of tangled light patterns. By creating billions of complex connections, or synapses, within the neural networks, we were able to recreate the primitive shapes of the light beams. This meant we had a way to create a decryption key that would be specific to each configuration of the encryption system .
Stelios Tzortzakis, Research Team Leader, University of Crete
The researchers used a high-power laser interacting with a small cuvette filled with ethanol to create a physical system that completely and chaotically entangles light beams. The liquid produced the desired turbulent behavior over a propagation distance of just a few millimeters at a reasonable cost.
The interaction of light with the liquid also exhibited thermal turbulence, which significantly increased turbulent entanglement and changed the intensity of the light beam.
Successful encryption and decryption
Researchers used a new method to encode and decode thousands of handwritten numbers and other shapes, such as tools, animals, and common objects, from renowned databases that serve as a benchmark for evaluating image retrieval systems.
They showed that the neural network could reliably recover encrypted images 90–95% of the time after modifying the testing process and training the network. They argue that this rate can be increased by training more accurate neural networks.
The researchers hope to advance the technology with additional security features, such as two-factor authentication. Since the size and cost of the laser system are major obstacles to commercialization, they are also looking for cheaper alternatives to expensive and cumbersome high-power lasers.
Link to the magazine:
Constantakis, P., et al . (2024) Optical information encoded in nonlinear chaotic systems discovered using neural networks. Optica doi.org/10.1364/optica.530643.
