Securing the post-quantum era: a review of quantum computing, blockchain and artificial intelligence for cybersecurity

Three technologies are changing what cybersecurity has to defend and what it can defend with. A large fault-tolerant quantum computer would break the public-key cryptography that protects most networks. Blockchains offer tamper-evident records without a central authority, yet they rest on the same threatened signatures. Artificial intelligence (AI) detects attacks at a speed analysts cannot match, and it also gives attackers new tools and new targets. This narrative review covers 150 sources on the three technologies and on their pairwise combinations. It summarizes the quantum threat and the resource estimates behind it, the post-quantum standards published by the National Institute of Standards and Technology in 2024, quantum key distribution, the attack surface of blockchains, and the use and abuse of machine learning in security. It then examines where the technologies meet: post-quantum ledgers, blockchain-coordinated federated learning, and quantum machine learning. Four findings follow. Migration to post-quantum cryptography is the only one of these changes with a deadline set by an adversary, so it should come first. Blockchains need the same migration and are harder to migrate than client-server systems. AI-based detection has value only when its training data, models and outputs are themselves protected. Quantum machine learning has no demonstrated security advantage yet. The review proposes a five-layer reference architecture, a procedure for ranking systems for cryptographic migration, and a list of open problems, with attention to organizations that have small security teams and limited budgets.