面向Hive的基于安全域的数据隔离保护框架
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  • 英文篇名:Security domain-based data isolation protection framework for Hive
  • 作者:常天天 ; 陈兴蜀 ; 罗永刚 ; 兰晓
  • 英文作者:CHANG Tian-tian;CHEN Xing-shu;LUO Yong-gang;LAN Xiao;College of Software Engineering,Sichuan University;College of Cybersecurity,Sichuan University;Cybersecurity Research Institute,Sichuan University;
  • 关键词:Hive ; 数据分级 ; 安全域 ; 访问控制
  • 英文关键词:Hive;;data classification;;security domain;;access control
  • 中文刊名:SDDX
  • 英文刊名:Journal of Shandong University(Natural Science)
  • 机构:四川大学计算机学院(软件学院);四川大学网络空间安全学院;四川大学网路空间安全研究院;
  • 出版日期:2019-02-28 11:15
  • 出版单位:山东大学学报(理学版)
  • 年:2019
  • 期:v.54
  • 基金:国家自然科学基金资助项目(61802270);; 国家“双创”示范基地之变革性技术国际研发转化平台资助(C700011);; 四川省重点研发项目资金资助(2018G20100);; 四川省科技支撑计划(2016GZ0038);; 中央高校基本科研业务费专项资金资助(2017SCU11059,2017SCU11065,SCU2016D009)
  • 语种:中文;
  • 页:SDDX201903001
  • 页数:9
  • CN:03
  • ISSN:37-1389/N
  • 分类号:5-13
摘要
针对Hive数据库中的数据共享所带来的敏感信息泄漏问题,以数据分级为前提,利用基于标签的访问控制技术,提出了一种基于安全域的数据隔离保护框架(SD-DIPF)。首先,通过设计层次安全标签树划分标签级别,用来对系统中的主客体进行标识;结合分级标签阐明安全域(SD)的设计思想,对安全域及其子域进行定义以及安全性的形式化证明;最后,利用安全域对平台数据进行逻辑划分保证不同敏感级别数据的有效隔离;针对该框架对Hive数据库的适用性进行说明,并结合现有的认证机制给出了其在Hive数据库中的实现。通过实验分析验证该框架可以保障敏感数据不被非法访问,证明了本框架的可行性和安全性。
        Aiming at the problem of sensitive information leakage caused by data sharing in Hive database, a data isolation and protection framework(SD-DIPF) based on security domain is proposed, which is combined with data classification and tag-based access control technology. Firstly, the tag level is divided by the hierarchy security tag tree which is used to identify the subject and object in the system. Then, the design idea of security domain(SD) is illustrated with hierarchical tags, the definition of SD and its subdomains and formal proof of security are given. Finally, the platform data is logically partitioned by security domain to ensure the effective isolation of different sensitive levels data. The applicability of SD-DIPF to Hive database is illustrated, and its implementation in Hive database is given based on the existing authentication mechanism. The experimental results show that SD-DIPF can protect sensitive data from being illegally accessed, which proves the feasibility and security of the framework.
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