TY - GEN
T1 - Revisiting Double-Spending Attacks on the Bitcoin Blockchain: New Findings
AU - Zheng, Jian
AU - Huang, Huawei
AU - Li, Canlin
AU - Zheng, Zibin
AU - Guo, Song
N1 - Funding Information:
This work described in this paper was supported by the Key-Area Research and Development Program of Guangdong Province (No.2019B020214006), the National Natural Science Foundation of China (No.62032025, No.61902445), and the Guangdong Basic and Applied Basic Research Foundation (No.2019A1515011798).
Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/25
Y1 - 2021/6/25
N2 - Bitcoin is currently the cryptocurrency with the largest market share. Many previous studies have explored the security of Bitcoin from the perspective of blockchain mining. Especially on the double-spending attacks (DSA), some state-of-the-art studies have proposed various analytical models, aiming to understand the insights behind the double-spending attacks. However, we believe that advanced versions of DSA can be developed to create new threats for the Bitcoin ecosystem. To this end, this paper mainly presents a new type of double-spending attack named Adaptive DSA in the context of the Bitcoin blockchain, and discloses the associated insights. In our analytical model, the double-spending attack is converted into a Markov Decision Process. We then exploit the Stochastic Dynamic Programming (SDP) approach to obtain the optimal attack strategies towards Adaptive DSA. Through the proposed analytical model and the disclosed insights behind Adaptive DSA, we aim to alert the Bitcoin ecosystem that the threat of double-spending attacks is still at a dangerous level.
AB - Bitcoin is currently the cryptocurrency with the largest market share. Many previous studies have explored the security of Bitcoin from the perspective of blockchain mining. Especially on the double-spending attacks (DSA), some state-of-the-art studies have proposed various analytical models, aiming to understand the insights behind the double-spending attacks. However, we believe that advanced versions of DSA can be developed to create new threats for the Bitcoin ecosystem. To this end, this paper mainly presents a new type of double-spending attack named Adaptive DSA in the context of the Bitcoin blockchain, and discloses the associated insights. In our analytical model, the double-spending attack is converted into a Markov Decision Process. We then exploit the Stochastic Dynamic Programming (SDP) approach to obtain the optimal attack strategies towards Adaptive DSA. Through the proposed analytical model and the disclosed insights behind Adaptive DSA, we aim to alert the Bitcoin ecosystem that the threat of double-spending attacks is still at a dangerous level.
KW - Bitcoin Blockchain
KW - Double-Spending Attack
UR - http://www.scopus.com/inward/record.url?scp=85115351216&partnerID=8YFLogxK
U2 - 10.1109/IWQOS52092.2021.9521306
DO - 10.1109/IWQOS52092.2021.9521306
M3 - Conference article published in proceeding or book
AN - SCOPUS:85115351216
T3 - 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021
SP - 1
EP - 6
BT - 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021
Y2 - 25 June 2021 through 28 June 2021
ER -