Quantum Random Number Generation for Cryptographic Applications

Project funded by Fundação para a Ciência e a Tecnologia, I.P. (FCT), grant 2022.09584.BD. Runs 2022-10-01 to 2026-09-30. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-07-23); national funding data, not CORDIS. Abstract given by the source: Quantum random number generation is a rapidly emerging technology that promises private high-quality randomness sources for many security-critical applications ranging from public-key cryptographic standards to secure multi-party computation. Nonetheless, practical implementations frequently rely on assumptions about the trustworthiness of the physical devices or sacrifice performance to achieve a high-security degree. In this proposal, we aim to develop a reliable self-testing (ST) randomness generation platform capable of throughputs suitable for practical applications. In this context, efforts to develop a novel high-performance ST theoretical framework will be taken. We will focus on achieving a proof-of-concept implementation and analyse aspects such as its performance, reliability, and security. Moreover, a detailed validation of the prototype will be made by proposing and implementing a set of cryptanalytic attacks effective against it. Finally, as a step toward a high-performance and cost-effective scheme, we aim to integrate the suitable components into a photonic integrated circuit.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Fundação para a Ciência e a Tecnologia, I.P. (FCT). Retrieved 2026-10-22. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: The project "Quantum Random Number Generation for Cryptographic Applications" is funded by FCT and runs from October 1, 2022, to September 30, 2026. It aims to develop a reliable self-testing randomness generation platform for security-critical applications. Suggested technology pillar: communication. Generated by AI from the public source text; it may contain errors and the original source is authoritative.