| 122 | 5 | 19 |
| Downloads | Citas | Reads |
Aimed at the data set with the same sensitive attribute values,the specific privacy disclosure was defined and its characteristics under homogeneity attack was studied.The concept and computing method of full instance disclosure risk were proposed,and the accurate measure of privacy disclosure with the same sensitive attribute values was achieved.The two generalization operation algorithms for data set with the same sensitive attribute values were designed,and the results of the same-disease data set were analyzed.The algorithm with an optimal result was chosen as the privacy protection method for the data set with the same sensitive attribute values.
[1]冯登国,张敏,李昊.大数据安全与隐私保护[J].计算机学报,2014,37(1):246-258.
[2]SWEENEY L.k-Anonymity:a model for protecting privacy[J].International journal of uncertainty,fuzziness and knowledgebased systems,2002,10(5):557-570.
[3]MACHANAVAJJHALA A,GEHRKE J,KIFER D,et al.l-Diversity:privacy beyond k-anonymity[C]//Proceedings of the22nd International Conference on Data Engineering.Atlanta,2006:24.
[4]LI N,LI T,VENKATASUBRAMANIAN S.t-Closeness:privacy beyond k-anonymity and l-diversity[C]//Proceedings of the23rd International Conference on Data Engineering.Istanbul,2007:106-115.
[5]WANG Q,ZENG Z P.(p,a)-Sensitive k-anonymity:privacy protection model[J].Application research of computers,2009,26(6):2176-2177.
[6]PRAKASH M,SINGARAVEL G.A new model for privacy preserving sensitive data mining[C]//Third International Conference on Computing Communication and Networking Technologies.Coimbatore,2012:1-8.
[7]LEFEVRE K,DEWITT D J,RAMAKRISHNAN R.Incognito:efficient full-domain k-anonymity[C]//Proceedings of the ACM SIGMOD International Conference on Management of Data.Baltimore,2005:49-60.
[8]YI T,SHI M Y,SHANG W Q,et al.Graded medical data publishing based on clustering[C]//Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery.Zhangjiajie,2015:1647-1652.
[9]WANG H Y,HAN J M,WANG J Y,et al.(l,e)-Diversity:a privacy preserving model to resist semantic similarity attack[J].Journal of computers,2014,9(1):59-64.
[10]许长清,赵华东,宋晓辉.基于大数据的电力用户群体识别与分析方法研究[J].郑州大学学报(理学版),2016,48(3):113-117.
[11]王伟,郭献彬.一种增强的匿名化隐私保护模型[J].信息通信,2016(1):1-4.
[12]彭瑞卿,刘行军,用户的行动轨迹还原与隐私风险度量[J].武汉大学学报(理学版),2017,63(2):142-150.
[13]杨晓春,刘向宇,王斌,等.支持多约束的k-匿名化方法[J].软件学报,2006,17(5):1222-1231.
[14]韩建民,岑婷婷,虞慧群.数据表k-匿名化的微聚集算法研究[J].电子学报,2008,36(10):2021-2029.
[15]LIU X P,LI X B,MOTIWALLA L,et al.Sharing patient disease data with privacy preservation[C]//Proceedings of the AIS SIGSEC Workshop on Information Security and Privacy.Fort Worth,2015:1-13.
[16]LIU X,LI X B,MOTIWALLA L,et al.Preserving patient privacy when sharing same-disease data[J].Journal of data and information quality,2016,7(4):17.
Basic Information:
DOI：10.13705/j.issn.1671-6841.2017291
China Classification Code:TP309
Citation Information:
[1]ZHENG Minghui,L Hanxiao,DUAN Yangyang ,et al.A Generalized Algorithm of Privacy Protection on Same Sensitive Value Data[J].Journal of Zhengzhou University(Natural Science Edition),2018,50(02):35-40.DOI:10.13705/j.issn.1671-6841.2017291.
Fund Information:
国家自然科学基金项目(61472121);; 湖北省创新群体项目(2016CFA021)
2018-01-24
2018-01-24
2018-01-24