Gate News message, on April 12, a researcher proposed a transaction scheme that enables quantum-resilient protection for Bitcoin without requiring a fork. At present, the quantum computing threat to Bitcoin is still at the theoretical level. Meanwhile, tech companies such as Google and Cloudflare have already begun preparing countermeasures and set a target timeline to complete the migration of quantum cryptography after 2029.

The Quantum-Safe Bitcoin (QSB) proposal put forward by StarkWare researcher Avihu Levy uses existing Bitcoin scripts to provide post-quantum security, avoiding a soft fork. QSB uses a Binohash-based construction and a “hash-to-signature” puzzle to defend against quantum computers’ attacks on elliptic curve cryptography. The scheme relies on RIPEMD-160’s preimage resistance, effectively strengthening the security of Bitcoin transactions.

StarkWare researchers proposed a quantum-safe Bitcoin scheme called QSB, aiming to replace the elliptic curve mechanism with hash assumptions to counter the threats posed by Shor’s algorithm. The scheme can run within existing scripts, requires no consensus changes, but does require submitting a transaction to a specific service.

Changpeng Zhao said in an interview that advances in quantum computing technology could threaten the security of existing cryptocurrencies, and that Bitcoin may need to adopt post-quantum encryption technology through a fork upgrade. He emphasized that the emergence of new encryption algorithms will help address the challenges posed by quantum computing.

Gate News message, on April 9, Strategy Executive Chairman Michael Saylor said that Bitcoin may have already bottomed out around $60k, as forced sellers have been gradually exiting the market. Saylor also expressed a cautious view of the security threat posed by quantum computing, saying that the relevant risks are still at a “theoretical level,” and that he believes the issue can be properly addressed in the future without overreacting.

Blockstream CEO Adam Back said in an interview that quantum computers have not yet threatened the Bitcoin network, but the industry needs to prepare in advance by migrating keys to a quantum-resistant format. He mentioned that his research team is pushing forward on related work; post-quantum cryptography has already entered the implementation stage. The challenge faced is how to complete the migration in an orderly way.

Former Google quantum hardware head John Martinis warns that Bitcoin could become a target for quantum computing attacks. Quantum computers could derive Bitcoin private keys within minutes, posing a greater threat than traditional financial systems. He recommends that the community plan quantum-resistance upgrades as early as possible to address threats over the next 5 to 10 years.

StarkWare announced on April 7 that Starknet is entering its fourth phase, aiming to improve network speed, decentralization, and privacy. New features include support for the STRK20 framework for ERC20 privacy, the strkBTC asset for redeemable Bitcoin, decentralized block validation, and progress toward full decentralization of the network. In addition, Starknet is also researching Bitcoin bridging solutions and promoting DeFi development, working toward achieving comprehensive quantum security.

Circle announced its post-quantum security roadmap for its Layer-1 Arc blockchain, aiming to ensure the security of wallets, signatures, validators, and off-chain infrastructure by before 2030. The roadmap is divided into four phases: the first phase will go live on the mainnet in 2026, using NIST-approved post-quantum signature schemes, highlighting the industry’s response to quantum threats. Arc offers a more concrete implementation plan than its competitors, marking a new advancement in security for the crypto industry.

BTQ Technologies publishes a research paper assessing the physical costs of quantum computing in Bitcoin mining, emphasizing that Bitcoin’s main risk comes from vulnerabilities in cryptographic signatures rather than quantum mining. The study proposes an open-source resource estimation model that covers key computational steps.