{"title":"区块链中的自私挖矿攻击:系统性文献综述","authors":"Nadisha Madhushanie, Sugandima Vidanagamachchi, Nalin Arachchilage","doi":"10.1007/s10207-024-00849-5","DOIUrl":null,"url":null,"abstract":"<p>Selfish mining is a sneaky way that some people cheat in blockchain networks or distributed digital ledger systems. They do it by mining a block in secret and keeping it hidden. Then, when the secret chain of these miners’ are longer than the real one, they show it to everyone, and the blockchain system selects the longest chain as the valid chain. This leads to the network adopting the longest chain as the valid one, resulting in the effort put into mining by other miners becoming futile. By doing this, selfish miners in the blockchain network have a high potential to get more rewards. This behavior goes against the rules of blockchain networks, where everyone is supposed to play by the same rules and have an equal chance of getting rewards. This prejudiced action of selfish miners have motivated us to investigate systematically the existing methods that are being used to address the selfish mining attacks. Therefore, we conducted a SLR (systematic literature review) of 29 papers using the Kitchenham methodology and put that into PRISMA framework. This study aims to investigate methods for detecting and mitigating selfish mining attacks, their limitations, and future directions.</p>","PeriodicalId":50316,"journal":{"name":"International Journal of Information Security","volume":"94 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Selfish mining attack in blockchain: a systematic literature review\",\"authors\":\"Nadisha Madhushanie, Sugandima Vidanagamachchi, Nalin Arachchilage\",\"doi\":\"10.1007/s10207-024-00849-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Selfish mining is a sneaky way that some people cheat in blockchain networks or distributed digital ledger systems. They do it by mining a block in secret and keeping it hidden. Then, when the secret chain of these miners’ are longer than the real one, they show it to everyone, and the blockchain system selects the longest chain as the valid chain. This leads to the network adopting the longest chain as the valid one, resulting in the effort put into mining by other miners becoming futile. By doing this, selfish miners in the blockchain network have a high potential to get more rewards. This behavior goes against the rules of blockchain networks, where everyone is supposed to play by the same rules and have an equal chance of getting rewards. This prejudiced action of selfish miners have motivated us to investigate systematically the existing methods that are being used to address the selfish mining attacks. Therefore, we conducted a SLR (systematic literature review) of 29 papers using the Kitchenham methodology and put that into PRISMA framework. This study aims to investigate methods for detecting and mitigating selfish mining attacks, their limitations, and future directions.</p>\",\"PeriodicalId\":50316,\"journal\":{\"name\":\"International Journal of Information Security\",\"volume\":\"94 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Information Security\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s10207-024-00849-5\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Security","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10207-024-00849-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Selfish mining attack in blockchain: a systematic literature review
Selfish mining is a sneaky way that some people cheat in blockchain networks or distributed digital ledger systems. They do it by mining a block in secret and keeping it hidden. Then, when the secret chain of these miners’ are longer than the real one, they show it to everyone, and the blockchain system selects the longest chain as the valid chain. This leads to the network adopting the longest chain as the valid one, resulting in the effort put into mining by other miners becoming futile. By doing this, selfish miners in the blockchain network have a high potential to get more rewards. This behavior goes against the rules of blockchain networks, where everyone is supposed to play by the same rules and have an equal chance of getting rewards. This prejudiced action of selfish miners have motivated us to investigate systematically the existing methods that are being used to address the selfish mining attacks. Therefore, we conducted a SLR (systematic literature review) of 29 papers using the Kitchenham methodology and put that into PRISMA framework. This study aims to investigate methods for detecting and mitigating selfish mining attacks, their limitations, and future directions.
期刊介绍:
The International Journal of Information Security is an English language periodical on research in information security which offers prompt publication of important technical work, whether theoretical, applicable, or related to implementation.
Coverage includes system security: intrusion detection, secure end systems, secure operating systems, database security, security infrastructures, security evaluation; network security: Internet security, firewalls, mobile security, security agents, protocols, anti-virus and anti-hacker measures; content protection: watermarking, software protection, tamper resistant software; applications: electronic commerce, government, health, telecommunications, mobility.