Asynchronous Quantum-Resistant Blockchain for Secure Intelligence Sharing
Yun-Yi Fan, Chit-Jie Chew, Jung-San Lee · Applied Sciences · 2025
By aggregating intelligence on emerging threats, attack techniques, and vulnerabilities, organizations can establish a more comprehensive threat landscape awareness and proactively identify potential risks. However, in the process of sharing threat intelligence, companies often hesitate due to concerns over information leakage, which reduces their willingness to collaborate. Furthermore, the lack of transparency and credibility in intelligence sources has negatively impacted the quality and trustworthiness of shared data. To address these issues, authors aim to leverage blockchain technology, utilizing its decentralized and tamper-proof properties to ensure corporate privacy and the reliability of intelligence sources. Additionally, a dual blockchain architecture is implemented to enhance operational efficiency and reduce storage burdens. However, with the advent of large-scale quantum computing, traditional cryptographic mechanisms used in blockchain systems face potential vulnerabilities due to Shor’s algorithm, which threatens widely adopted public key cryptographic schemes. To ensure long-term security and resilience in a quantum-enabled threat landscape, quantum-resistant cryptographic technologies, including SPHINCS+ and CRYSTALS-KYBER, are integrated to facilitate quantum-safe migration in blockchain applications, ensuring system security and resilience in future environments of quantum computing.