摘要
针对基于角色的访问控制(role-based access control,RBAC)中的约束问题,提出一种基于双重约束的角色挖掘算法。将用户权限分配关系转化为二分图表示,在约束条件下,利用二分图中寻找最小完全二分图覆盖的方法,得到满足权限基数约束和用户基数约束的初始角色集,通过图优化的方法优化角色状态构建角色层次,得到最终的角色集。实验结果表明,利用该算法得到的角色集,能够有效实施约束策略,保证RBAC系统的安全。
Aiming at the constraint problem in role-based access control(RBAC),a role mining algorithm based on double constraint was proposed.The user permissions assignment relationship was transformed into a bipartite graph representation.Under the constraint condition,the method of finding the minimum complete bipartite graph coverage in the bipartite graph was used to obtain the initial character set that satisfied the authority base constraint and the user base constraint.The role state was optimized using graph optimization method to build the role hierarchy and get the final character set.Experimental results show that the character set obtained using the algorithm can effectively implement the constraint strategy and ensure the security of the RBAC system.
作者
王静宇
崔永娇
谭跃生
WANG Jing-yu;CUI Yong-jiao;TAN Yue-sheng(School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou 014010,China)
出处
《计算机工程与设计》
北大核心
2020年第6期1599-1604,共6页
Computer Engineering and Design
基金
国家自然科学基金项目(61662056)
内蒙古自然科学基金项目(2016MS0609、2016MS0608)。
关键词
基于角色访问控制
角色挖掘
约束
二分图
图优化
role-based access control
role mining
constraint
bipartite graph
graph optimization
