TY - EJOU AU - Zhang, Weijian AU - Wang, Hao AU - Hua, Hao AU - Wang, Qirun TI - Selfish Mining and Defending Strategies in the Bitcoin T2 - Intelligent Automation \& Soft Computing PY - 2022 VL - 34 IS - 3 SN - 2326-005X AB - As a kind of distributed, decentralized and peer-to-peer transmitted technology, blockchain technology has gradually changed people’s lifestyle. However, blockchain technology also faces many problems including selfish mining attack, which causes serious effects to the development of blockchain technology. Selfish mining is a kind of mining strategy where selfish miners increase their profit by selectively publishing hidden blocks. This paper builds the selfish mining model from the perspective of node state conversion and utilize the function extremum method to figure out the optimal profit of this model. Meanwhile, based on the experimental data of honest mining, the author conducts the simulation of selfish mining and discovers that selfish miners are able to acquire more revenue than honest miners when they account for more than 1/3 computing power of the whole system. Lastly, to defend the selfish mining attack, the author also summarizes the existing defending strategies and evaluates every kind of strategy briefly. KW - Bitcoin; blockchain; selfish mining; markov chain DO - 10.32604/iasc.2022.030274