In this paper, we first propose an adaptive strategy for double-spending attack on blockchains. The attacker in our strategy observes the length of the honest branch when a submitted transaction becomes available in the blockchain, and then updates the attack strategy accordingly. This provides a stronger strategy than conventional double-spending attack. We then derive closed-form expressions for the probability of a successful attack and the expected reward of attacker miners. Our analysis shows that the probability of a successful attack by convincing the network nodes to follow the counterfeit branch under the proposed attack strategy is 60% higher than what is expected from the conventional attack strategy when the attackers acquire 40% of the total network processing power. To counter this increase in the probability of attack, the network nodes are required to use a bigger number of confirmation blocks for validating any transaction in the blockchain. We computed the expected reward of an attacker for mining a counterfeit branch on a blockchain and observed that the expected reward drops to zero after a few number of block confirmations.
Index Terms—blockchain, double-spending, security, attack
Gholamreza Ramezanl; Cyril Leung; and Z. Jane Wang, "A Strong Adaptive Strategic Double-spending Attack on Blockchains," IEEE Blockchain Conference, Halifax, N.S., Canada, July 27-Aug 3, 2018.