Advanced Search
Volume 42 Issue 5
Jun.  2020
Turn off MathJax
Article Contents
Jiang Yu-Wen, Tan Le-Yi, Wang Shou-Jue. Saliency Detected Model Based on Selective Edges Prior[J]. Journal of Electronics & Information Technology, 2015, 37(1): 130-136. doi: 10.11999/JEIT140119
Citation: Peili LI, Haixia XU. Blockchain User Anonymity and Traceability Technology[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1061-1067. doi: 10.11999/JEIT190813

Blockchain User Anonymity and Traceability Technology

doi: 10.11999/JEIT190813
Funds:  The National Key R&D Program of China (2017YFB0802500), Beijing Municipal Science and Technology Project (Z191100007119007), The Major Science and Technology Innovation Project of Shandong Province (2019JZZY020129)
  • Received Date: 2019-10-22
  • Rev Recd Date: 2020-01-20
  • Available Online: 2020-02-25
  • Publish Date: 2020-06-04
  • Blockchain has the advantages of transparency, data integrity, tamper resistance, etc., and has important application value to the fields of finance, government, and military. There are many work to study the privacy protection of the blockchain, typically including Monero, Zerocash, Mixcoin, and more. Their privacy protection methods can be used to protect the identity of the user and the amount of the transaction. The privacy protection scheme is a double-edged sword. On the one hand, it is the perfect protection of the privacy of legitimate users. On the other hand, if it is completely out of supervision, it is the appeasement and connivance of illegal crimes such as money laundering and extortion. In response to the various endangered privacy protection schemes on the blockchain, regulation must also keep pace with the times. In view of this, the privacy protection and supervision methods of blockchain user’s identity is studied, and anonymity and traceability technology to promote the application of blockchain to practice is proposed.
  • NAKAMOTO S. Bitcoin: A peer-to-peer electronic cash system[EB/OL]. https://bitcoin.org/bitcoin.pdf, 2008.
    曹素珍, 王斐, 郎晓丽, 等. 基于无证书的多方合同签署协议[J]. 电子与信息学报, 2019, 41(11): 2691–2698. doi: 10.11999/JEIT190166

    CAO Suzhen, WANG Fei, LANG Xiaoli, et al. Multi-party contract signing protocol based on certificateless[J]. Journal of Electronics &Information Technology, 2019, 41(11): 2691–2698. doi: 10.11999/JEIT190166
    NARAYANAN A, BONNEAU J, FELTEN E, et al. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction[M]. Princeton University Press, 2016.
    牛淑芬, 王金风, 王伯彬, 等. 区块链上基于B+树索引结构的密文排序搜索方案[J]. 电子与信息学报, 2019, 41(10): 2409–2415. doi: 10.11999/JEIT190038

    NIU Shufen, WANG Jinfeng, WANG Bobin, et al. Ciphertext sorting search scheme based on b+ tree index structure on blockchain[J]. Journal of Electronics &Information Technology, 2019, 41(10): 2409–2415. doi: 10.11999/JEIT190038
    邹均, 张海宁, 唐屹, 等. 区块链技术指南[M]. 北京: 机械工业出版社, 2016: 97–99.

    ZOU Jun, ZHANG Haining, TANG Yi, et al. Guidelines for Blockchain Technology[M]. Beijing: China Machine Press, 2016: 97–99.
    CHAUM D, FIAT A, and NAOR M. Untraceable Electronic Cash[M]. GOLDWASSER S. Advances in Cryptology — CRYPTO’ 88. New York: Springer, 1990: 319–327. doi: 10.1007/0-387-34799-2_25.
    CHAUM D and VAN HEYST E. Group Signatures[M]. DAVIES D W. Advances in Cryptology — EUROCRYPT ’91. Berlin: Springer, 1991: 257–265. doi: 10.1007/3-540-46416-6_22.
    GROTH J and SAHAI A. Efficient non-interactive proof systems for bilinear groups[C]. The 27th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Istanbul, Turkey, 2008: 415–432. doi: 10.1007/978-3-540-78967-3_24.
    CHAUM D L. Untraceable electronic mail, return addresses, and digital pseudonyms[J]. Communications of the ACM, 1981, 24(2): 84–90. doi: 10.1145/358549.358563
    BONNEAU J, NARAYANAN A, MILLER A, et al. Mixcoin: Anonymity for Bitcoin with Accountable Mixes[M]. CHRISTIN N and SAFAVI-NAINI R. Financial Cryptography and Data Security. Berlin: Springer, 2014: 486–504. doi: 10.1007/978-3-662-45472-5_31.
    VALENTA L and ROWAN B. BLIndcoin: Blinded, accountable mixes for bitcoin[C]. 2015 International Conference on Financial Cryptography and Data Security, San Juan, USA, 2015: 112–126. doi: 10.1007/978-3-662-48051-9_9.
    MAXWELL G. Coinjoin: Bitcoin privacy for the real world[EB/OL]. Post on Bitcoin Forum. https://bitcointalk.org/index.php?topic=279249.0, 2013.
    RUFFING T, MORENO-SANCHEZ P, and KATE A. CoinShuffle: Practical decentralized coin mixing for bitcoin[C]. The 19th European Symposium on Research in Computer Security, Wroclaw, Poland, 2014: 345–364. doi: 10.1007/978-3-319-11212-1_20.
    RUFFING T, MORENO-SANCHEZ P, and KATE A. P2P mixing and unlinkable bitcoin transactions[C]. The 24th Annual Network and Distributed System Security Symposium, San Diego, USA, 2017: 824.
    RUFFING T and MORENO-SANCHEZ P. Valueshuffle: Mixing confidential transactions for comprehensive transaction privacy in bitcoin[C]. 2017 International Conference on Financial Cryptography and Data Security, Sliema, Malta, 2017: 133–154.
    CHANDRAN N, GROTH J, and SAHAI A. Ring signatures of sub-linear size without random oracles[C]. The 34th International Colloquium on Automata, Languages, and Programming, Wrocław, Poland, 2007: 423–434.
    BERGAN T, ANDERSON O, DEVIETTI J, et al. CryptoNote v 2.0[J]. https://cryptonote.org/whitepaper.pdf, 2013.
    LIU J K, WEI V K, and WONG D S. Linkable spontaneous anonymous group signature for ad hoc groups[C]. The 9th Australasian Conference on Information Security and Privacy, Sydney, Australia, 2004: 325–335. doi: 10.1007/978-3-540-27800-9_28.
    MIERS I, GARMAN C, GREEN M, et al. Zerocoin: Anonymous distributed e-cash from bitcoin[C]. 2013 IEEE Symposium on Security and Privacy, Berkeley, USA, 2013: 397–411.
    BEN SASSON E, CHIESA A, GARMAN C, et al. Zerocash: Decentralized anonymous payments from bitcoin[C]. 2014 IEEE Symposium on Security and Privacy, San Jose, USA, 2014: 459–474.
    BEN-SASSON E, CHIESA A, TROMER E, et al. Succinct non-interactive zero knowledge for a von Neumann architecture[C]. The 23rd USENIX Conference on Security Symposium, Berkeley, USA, 2014: 781–796.
    PEDERSEN T P. Non-interactive and information-theoretic Secure Verifiable Secret Sharing[M]. FEIGENBAUM J. Annual International Cryptology— CRYPTO ’91. Berlin: Springer, 1991: 129–140. doi: 10.1007/3-540-46766-1_9.
    FUJISAKI E and SUZUKI K. Traceable ring signature[C]. The 10th International Conference on Practice and Theory in Public-Key Cryptography, Beijing, China, 2007: 181–200. doi: 10.1007/978-3-540-71677-8_13.
    GROTH J. Fully anonymous group signatures without random oracles[C]. The 13th International Conference on the Theory and Application of Cryptology and Information Security, Kuching, Malaysia, 2007: 164–180. doi: 10.1007/978-3-540-76900-2_10.
    ZHOU Sujing and LIN Dongdai. Shorter Verifier-local Revocation Group Signatures from Bilinear Maps[M]. POINTCHEVAL D, MU Yi, and CHEN Kefei. Cryptology and Network Security. Berlin: Springer, 2006: 126–143. doi: 10.1007/11935070_8.
    BONEH D and BOYEN X. Short Signatures without Random Oracles[M]. CACHIN C and CAMENISCH J L. Advances in Cryptology - EUROCRYPT 2004. Berlin: Springer, 2004: 56–73. doi: 10.1007/978-3-540-24676-3_4.
  • Cited by

    Periodical cited type(20)

    1. 周晨,周乾伟,陈翰墨,管秋,胡海根,吴延壮. 面向RGBD图像显著性检测的循环逐尺度融合网络. 小型微型计算机系统. 2023(10): 2276-2283 .
    2. 叶海峰,赵玉琛. 视觉位置识别中代表地点的标识牌算法. 小型微型计算机系统. 2021(04): 823-828 .
    3. 王慧玲,宋鑫怡,杨颖. 基于优化查询的改进显著性检测算法. 吉林大学学报(信息科学版). 2020(03): 319-324 .
    4. 郭迎春,李卓. 基于边缘特征和自适应融合的视频显著性检测. 河北工业大学学报. 2019(01): 1-7 .
    5. 鲁文超,段先华,徐丹,王万耀. 基于多尺度下凸包改进的贝叶斯模型显著性检测算法. 计算机科学. 2019(06): 295-300 .
    6. 王宝艳,张铁,李凯,杜松林. DEL分割算法对SSLS算法的改进. 小型微型计算机系统. 2019(10): 2052-2057 .
    7. 张巧荣,徐国愚,张俊峰. 利用视觉显著性的前景目标分割. 兰州大学学报(自然科学版). 2019(06): 833-840 .
    8. 杨俊丰,林亚平,欧博,蒋军强,李强. 基于显著性加权随机优化的快速响应码美化方法. 电子与信息学报. 2018(02): 289-297 . 本站查看
    9. 邓晨,谢林柏. 全局对比和背景先验驱动的显著目标检测. 计算机工程与应用. 2018(03): 212-216 .
    10. 刘亚宁,吴清,魏雪. 基于流行排序的前景背景显著性检测算法. 科学技术与工程. 2018(18): 74-81 .
    11. 闫钧华,肖勇旗,姜惠华,杨勇,张寅. 融合区域像素显著性和时域信息的地面动目标检测及其DSP实现. 电子设计工程. 2018(19): 178-183+193 .
    12. 陈厚仁,蔡延光. 基于视频的干线交通流检测系统的研究与实现. 工业控制计算机. 2017(07): 85-87 .
    13. 赵艳艳,沈西挺. 基于同步更新的背景检测显著性优化. 计算机工程. 2017(10): 264-267 .
    14. 田畅,姜青竹,吴泽民,刘涛,胡磊. 基于区域协方差的视频显著度局部空时优化模型. 电子与信息学报. 2016(07): 1586-1593 . 本站查看
    15. 罗会兰,万成涛,孔繁胜. 基于KL散度及多尺度融合的显著性区域检测算法. 电子与信息学报. 2016(07): 1594-1601 . 本站查看
    16. 张晴,林家骏,戴蒙. 基于图的流行排序的显著目标检测改进算法. 计算机工程与应用. 2016(22): 26-32+38 .
    17. 杜永强. 过度曝光图像缺失信息修复算法. 科技通报. 2016(08): 146-149 .
    18. 郎波,樊一娜,黄静. 利用混合高斯进行物体成分拟合匹配的算法. 科学技术与工程. 2016(20): 73-80 .
    19. 项导,侯赛辉,王子磊. 基于背景学习的显著物体检测. 中国图象图形学报. 2016(12): 1634-1643 .
    20. 吕建勇,唐振民. 一种基于图的流形排序的显著性目标检测改进方法. 电子与信息学报. 2015(11): 2555-2563 . 本站查看

    Other cited types(21)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(2)

    Article Metrics

    Article views (4910) PDF downloads(461) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return