江苏大学学报（自然科学版）2017，Vol.38Issue(1)：78-85,8.DOI:10.3969/j.issn.1671-7775.2017.01.014
面向SVM的隐私保护方法研究进展
Research progress of privacy-preserving support vector machines
摘要
Abstract
To realize information security for future support vector machines (SVM)data mining,the privacy-preserving support vector machines (PPSVM) was investigated to obtain effective result.The characteristics of SVMclassifiers were analyzed to find the security hole.The latest literatures and related research were summarized. The recent progress of privacy-preserving support vector machines was presented based on data perturbation and data encryption.The future hot research directions of new privacy-preserving support vector machine technologies in distributed environment,more effective fully homomorphic encryption(FHE)schemes and privacy-preserving support vector machine technologies for big data mining were pointed out.关键词
隐私保护/支持向量机/安全多方计算/同态加密/大数据Key words
privacy preserving/SVM/secure multi-party computation/homomorphic encryption/big data分类
信息技术与安全科学引用本文复制引用
彭晓冰,李启顺,王丽珍,朱玉全..面向SVM的隐私保护方法研究进展[J].江苏大学学报（自然科学版）,2017,38(1):78-85,8.基金项目
国家自然科学基金资助项目（71271117）；江苏省六大人才高峰项目（2013-WLW-005）；江苏省自然科学基金资助项目（BK20150531）；江苏省高校研究生科研创新计划项目 （）
