通信学报 ›› 2019, Vol. 40 ›› Issue (4): 83-94.doi: 10.11959/j.issn.1000-436x.2019077
修回日期:
2019-02-04
出版日期:
2019-04-25
发布日期:
2019-05-05
作者简介:
王斌(1979-),男,黑龙江安达人,哈尔滨工程大学博士生,佳木斯大学副教授,主要研究方向为机器学习、隐私保护。|张磊(1982-),男,黑龙江绥化人,博士,佳木斯大学副教授,主要研究方向为信息安全、隐私保护。|张国印(1962-),男,博士,山东黄县人,哈尔滨工程大学教授、博士生导师,主要研究方向为嵌入式系统与体系结构、网络技术与信息安全。
基金资助:
Bin WANG1,2,Lei ZHANG2(),Guoyin ZHANG1
Revised:
2019-02-04
Online:
2019-04-25
Published:
2019-05-05
Supported by:
摘要:
针对路网环境下mix-zone无法有效地实现属性进行隐藏或泛化和抵御伪装攻击的问题,基于属性泛化和同态加密,提出了一种秘态属性泛化的隐私保护方法。该方法通过同态加密,实现了秘密出价选择计算代理、秘密计算相似属性,并以相似属性完成属性泛化的整体处理。通过属性泛化,解决了mix-zone可被攻击者利用属性追踪的问题,同时秘密计算的属性处理不会泄露任何信息给参与者,也防止伪装攻击者获得mix-zone中各用户的隐私信息。最后,通过安全性分析和实验验证分别在理论和实践这2个方面对所提算法的优势加以分析和比较。
中图分类号:
王斌,张磊,张国印. 基于多方安全计算的属性泛化mix-zone[J]. 通信学报, 2019, 40(4): 83-94.
Bin WANG,Lei ZHANG,Guoyin ZHANG. Attribute generalization mix-zone based on multiple secure computation[J]. Journal on Communications, 2019, 40(4): 83-94.
表1
5种算法在不同用户数量下的信息熵"
算法 | 用户数量为5 | 用户数量为10 | 用户数量为15 | 用户数量为20 | 用户数量为25 | 用户数量为30 |
等待忍耐mix-zone | 2.089 7 | 2.989 7 | 3.516 2 | 3.889 7 | 4.179 5 | 4.416 2 |
偏移mix-zone | 2.136 2 | 3.056 2 | 3.594 3 | 3.976 2 | 4.272 3 | 4.514 3 |
多维mix-zone | 2.275 5 | 3.255 5 | 3.828 8 | 4.235 5 | 4.551 0 | 4.808 8 |
加密mix-zone | 2.205 8 | 3.155 8 | 3.711 5 | 4.105 8 | 4.411 7 | 4.661 5 |
AG mix-zone | 2.321 9 | 3.321 9 | 3.906 9 | 4.321 9 | 4.643 9 | 4.906 9 |
表2
5种算法在不同用户数量下的成对信息熵"
算法 | 用户数量为5 | 用户数量为10 | 用户数量为15 | 用户数量为20 | 用户数量为25 | 用户数量为30 |
等待忍耐mix-zone | 0.244 5 | 0.133 1 | 0.084 4 | 0.067 0 | 0.053 9 | 0.050 3 |
偏移mix-zone | 0.253 9 | 0.153 5 | 0.110 3 | 0.086 5 | 0.073 1 | 0.063 0 |
多维mix-zone | 0.365 6 | 0.237 1 | 0.184 0 | 0.153 7 | 0.133 7 | 0.119 3 |
加密mix-zone | 0.446 2 | 0.311 2 | 0.257 4 | 0.223 6 | 0.199 6 | 0.182 6 |
AG mix-zone | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
表3
随用户数量变化的算法执行时间对比(规则mix-zone)"
算法 | 用户数量为5 | 用户数量为10 | 用户数量为15 | 用户数量为20 | 用户数量为25 | 用户数量为30 |
等待忍耐mix-zone | 0.395 3 | 0.399 1 | 0.399 6 | 0.399 8 | 0.3998 | 0.399 9 |
偏移mix-zone | 0.379 2 | 0.392 1 | 0.395 5 | 0.397 0 | 0.3978 | 0.398 3 |
多维mix-zone | 0.371 0 | 0.387 4 | 0.392 2 | 0.394 5 | 0.3958 | 0.396 6 |
加密mix-zone | 0.315 8 | 0.381 2 | 0.511 3 | 0.551 2 | 0.5874 | 0.617 1 |
AG mix-zone | 0.339 3 | 0.478 1 | 0.541 8 | 0.586 1 | 0.720 6 | 0.741 1 |
表4
随用户数变化的算法执行成功率对比(不规则mix-zone)"
算法 | 用户数量为5 | 用户数量为10 | 用户数量为15 | 用户数量为20 | 用户数量为25 | 用户数量为30 |
等待忍耐mix-zone | 87.87% | 81.97% | 76.62% | 70.33% | 64.36% | 52.78% |
偏移mix-zone | 88.19% | 83.68% | 81.85% | 78.00% | 71.78% | 64.39% |
多维mix-zone | 88.88% | 86.84% | 84.19% | 81.05% | 82.50% | 78.56% |
加密mix-zone | 88.69% | 86.00% | 82.33% | 82.88% | 77.73% | 76.91% |
AG mix-zone | 89.30% | 88.31% | 87.42% | 86.33% | 85.20% | 83.98% |
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