The 51% Attack on Blockchains: A Mining Behavior Study

被引:65
作者
Aponte-Novoa, Fredy Andres [1 ,2 ]
Orozco, Ana Lucila Sandoval [1 ,3 ]
Villanueva-Polanco, Ricardo [1 ]
Wightman, Pedro [4 ]
机构
[1] Univ Norte, Dept Comp Sci & Engn, Barranquilla 081001, Colombia
[2] Univ Santo Tomas, Dept Syst Engn, Tunja 150009, Colombia
[3] Univ Complutense Madrid UCM, Fac Comp Sci & Engn, Dept Software Engn & Artificial Intelligence DIS, Grp Anal Secur & Syst GASS, Off 431, Madrid 28040, Spain
[4] Univ Rosario, Escuela Ingn Ciencia & Tecnol, Bogota 111711, Colombia
关键词
Blockchains; Bitcoin; Consensus algorithm; Computer science; Proof of Work; Proposals; Licenses; 51% attack; bitcoin; blockchain; double-speding; ethereum; hash rate; PROOF;
D O I
10.1109/ACCESS.2021.3119291
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The applications that use blockchain are cryptocurrencies, decentralized finance applications, video games, and many others. Most of these applications trust that the blockchain will prevent issues like fraud, thanks to the built-in cryptographic mechanisms provided by the data structure and the consensus protocol. However, blockchains suffer from what is called a 51% attack or majority attack, which is considered a high risk for the integrity of these blockchains, where if a miner, or a group of them, has more than half the computing capability of the network, it can rewrite the blockchain. Even though this attack is possible in theory, it is regarded as hard-achievable in practice, due to the assumption that, with enough active members, it is very complicated to have that much computing power; however, this assumption has not been studied with enough detail. In this work, a detailed characterization of the miners in the Bitcoin and Crypto Ethereum blockchains is presented, with the aim of proving the computing distribution assumption and creating profiles that may allow the detection of anomalous behaviors and prevent 51% attacks. The results of the analysis show that, in the last years, there has been an increasing concentration of hash rate power in a very small set of miners, which generates a real risk for current blockchains. Also, that there is a pattern in mining among the main miners, which makes it possible to identify out-of-normal behavior.
引用
收藏
页码:140549 / 140564
页数:16
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