[ "祝烈煌(1976-),男,博士,北京理工大学计算机学院教授、副院长、博士生导师,网络与信息安全研究所所长,主要研究方向为密码算法与安全协议、区块链技术、大数据隐私保护等。" ]
[ "董慧(1993-),女,北京理工大学计算机学院硕士生,主要研究方向为区块链应用与隐私保护。" ]
[ "沈蒙(1988-),男,博士,北京理工大学计算机学院讲师、硕士生导师,主要研究方向为数据安全共享与隐私保护。" ]
网络首发:2018-01,
纸质出版:2018-01-15
移动端阅览
祝烈煌, 董慧, 沈蒙. 区块链交易数据隐私保护机制[J]. 大数据, 2018,4(1):2018005.
Liehuang ZHU, Hui DONG, Meng SHEN. Privacy protection mechanism for blockchain transaction data[J]. Big Data Research, 2018, 4(1): 2018005.
祝烈煌, 董慧, 沈蒙. 区块链交易数据隐私保护机制[J]. 大数据, 2018,4(1):2018005. DOI: 10.11959/j.issn.2096-0271.2018005.
Liehuang ZHU, Hui DONG, Meng SHEN. Privacy protection mechanism for blockchain transaction data[J]. Big Data Research, 2018, 4(1): 2018005. DOI: 10.11959/j.issn.2096-0271.2018005.
区块链技术是一种去中心化、去信任化、公开透明的分布式数据存储技术,能够降低信任成本,实现安全可靠的数据交互。然而,攻击者可以轻易地从公开的全局账本中获得所有数据,并通过大数据分析技术挖掘用户交易规律等隐私信息。分析区块链交易数据面临的隐私泄露威胁,描述基于数据分析的攻击方法;介绍以混币机制为代表的交易数据隐私保护机制,简要描述各种混币方法的基本原理,并针对混币过程是否需要中心节点参与的问题分析不同混币机制的优势与缺陷;最后,分析了现有区块链数据隐私保护技术中存在的不足,并展望未来的发展方向。
Blockchain technology is a distributed data storage technology that is de-centralized
de-trusted
open and transparent.It can reduce the cost of trust and realize safe and reliable data interaction.However
attackers can easily obtain the transaction data stored in the public ledger
and may extract transaction rules and other privacy information from this data by applying big data analysis techniques.Firstly
the thread of attack of data analysis on blockchain transaction data was analyzed
and the attack methods based on data analysis were described.Then the privacy protection mechanism of transaction data which was represented by mixing mechanism was introduced
the basic principle of various mixing methods was described in brief
and the advantages and disadvantages of different mixing approaches for the problem of whether a central node was needed in the process of mixing were analyzed.In the end
the limitation of the existing technologies and envision the future directions on this topic was discussed.
REID F , HARRIGAN M . An analysis of anonymity in the Bitcoin system [C ] // The 2011 IEEE Third International Conference on Privacy,Security,Risk and Trust,October 9-11,2011,Boston,USA . Piscataway:IEEE Press , 2011 : 1318 - 1326 .
LIAO K , ZHAO Z , DOUPE A , et al . Behind closed doors:measurement and analysis of CryptoLocker ransoms in Bitcoin [C ] // The Symposium on Electronic Crime Research,June 1-3,2016,Toronto,Canada . Piscataway:IEEE Press , 2016 : 1 - 13 .
RON D , SHAMIR A . Quantitative analysis of the full Bitcoin transaction graph [C ] // The 17th International Conference on Financial Cryptography and Data Security,April 1-5,2013,Okinawa,Japan . Heidelberg:Springer , 2013 : 6 - 24 .
MEIKLEJOHN S , POMAROLE M , JORDAN G , et al . A fistful of bitcoins:characterizing payments among men with no names [C ] // The 13th ACM Internet Measurement Conference,October 23-25,2013,Barcelona,Spain . New York:ACM Press , 2013 : 127 - 140 .
ZHAO C . Graph-based forensic investigation of Bitcoin transactions [D ] . Iowa:Iowa State University , 2014 .
DWORK C , NAOR M . Pricing via processing or combatting junk mail [C ] // The 12th Annual International Cryptology Conference on Advances in Cryptology,August 16-20,1992,Santa Barbara,USA . Piscataway:IEEE Press , 1992 : 139 - 147 .
CASTRO M , LISKOV B . Practical byzantine fault tolerance and proactive recovery [J ] . ACM Transactions on Computer Systems , 2002 , 20 ( 4 ): 398 - 461 .
ANDROULAKI E , KARAME G O , ROESCHLIN M , et al . Evaluating user privacy in Bitcoin [C ] // The 17th International Conference on Financial Cryptography and Data Security,April 1-5,2013,Okinawa,Japan . Heidelberg:Springer , 2013 : 34 - 51 .
MONACO J V , . Identifying Bitcoin users by transaction behavior [C ] // The SPIE DSS,April 20-25,2015,Baltimore,USA . Baltimore:SPIE , 2015 .
CHAUM D . Untraceable electronic mail,return addresses and digital pseudonyms [J ] . Communications of the ACM , 2003 : 211 - 219 .
BONNEAU J , NARAYANAN A , MILLER A , et al . Mixcoin:anonymity for Bitcoin with accountable mixes [C ] // The 19th International Conference on Financial Cryptography and Data Security,January 26-30,2015,San Juan,Argentina . Barbados:Financial Cryptography , 2014 : 486 - 504 .
VALENTA L , ROWAN B . Blindcoin:blinded,accountable mixes for Bitcoin [J ] . Financial Cryptography and Data Security , 2015 : 112 - 126
SHENTU Q C , YU J P . A blind-mixing scheme for Bitcoin based on an elliptic curve cryptography blind digital signature algorithm [J ] . Computer Science , 2015 .
RUFFING T,MORENO-SANCHEZ P , KATE A . CoinShuffle:practical decentralized coin mixing for Bitcoin [M ] // Computer Security -ESORICS 2014,Heidelberg:Springer , 2014 : 345 - 364 .
BISSIAS G , OZISIK A P , LEVINE B N , et al . Sybil-resistant mixing for Bitcoin [C ] // The 2015 ACM Workshop on Privacy in the Electronic Society,November 3,2014,Scottsdale,USA . New York:ACM Press , 2014 : 149 - 158 .
ZIEGELDORF J H , GROSSMANN F , HENZE M , et al . CoinParty:secure multi-party mixing of Bitcoins [C ] // The 5th ACM Conference on Data and Application Security and Privacy,March 2-4,2015,San Antonio,USA . New York:ACM Press , 2015 : 75 - 86 .
DANEZIS G , FOURNET C , KOHLWEISS M , et al . Pinocchio coin:building zerocoin from a succinct pairing-based proof system [C ] // ACM Workshop on Language Support for Privacy-Enhancing Technologies,November 4,2013,Berlin,Germany . New York:ACM Press , 2013 : 27 - 30 .
SASSON E B , CHIESA A , GARMAN C , et al . Zerocash:decentralized anonymous payments from Bitcoin [C ] // The 2014 IEEE Symposium on Security and Privacy,May 18-21,2014,Berkeley,USA . Washington:IEEE Computer Society , 2014 : 459 - 474 .
0
浏览量
2577
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621