The Bitcoin Heist: How Quantum Computers Can Steal Your Cryptocurrency in Under 10 Minutes

The first part of this series explored the fundamentals of quantum computing, but understanding how it can be utilized to steal bitcoin requires knowledge of what it's attacking and where the vulnerability lies. This piece begins with an examination of bitcoin's encryption, working its way through to the nine-minute window identified by Google's recent quantum computing paper. Bitcoin employs elliptic curve cryptography, which involves a private key and a public key derived from it through a mathematical operation. The process can be thought of as a one-way map, where starting from a known point, taking a certain number of steps leads to the public key, but reversing this process is virtually impossible for classical computers. However, Shor's algorithm, a quantum algorithm discovered in 1994, can efficiently solve this problem by finding the period of a function related to the elliptic curve. This is achieved by utilizing the principles of superposition, entanglement, and interference in quantum mechanics. The recent paper by Google reduced the estimated number of qubits required to run Shor's algorithm against bitcoin's elliptic curve from millions to fewer than 500,000, making the threat more tangible. The paper also introduced a practical attack scenario where parts of the calculation can be precomputed, leaving only the second half to be completed once a target public key is identified. This second half is estimated to take around nine minutes, which is close to bitcoin's average block confirmation time. Therefore, if a user broadcasts a transaction with their public key visible, a quantum attacker has a roughly 41% chance of deriving the private key and submitting a competing transaction within the nine-minute window. Moreover, approximately 6.9 million bitcoin are vulnerable to an 'at-rest' attack since their public keys have already been exposed on the blockchain. The implications of this vulnerability and the ongoing advancements in quantum computing hardware will be discussed in the next part of this series.