计算机科学 ›› 2018, Vol. 45 ›› Issue (12): 117-122.doi: 10.11896/j.issn.1002-137X.2018.12.018
周超1,2,3,4, 任志宇1,2,3, 毋文超1,2,3
ZHOU Chao1,2,3,4, REN Zhi-yu1,2,3, WU Wen-chao1,2,3
摘要: 基于角色的访问控制(Role-Based Access Control,RBAC)在管理和安全方面具有优势,经过20多年的发展后已被广泛应用于各个领域,如何将数据繁多的非RBAC系统迁移成RBAC系统已经成为一个意义重大的难题。角色是RBAC的基本特征,因此角色挖掘是RBAC系统实施的一个重要环节。基于形式概念分析生成用户权限概念格及用户属性概念格,将用户权限概念格翻转后映射为初始候选角色状态,通过约简操作和精简操作来挖掘角色,然后对用户权限概念格及用户属性概念格进行相似性分析,通过定义最近似表达式为角色赋予语义,使得生成的角色具有以下两点优势:1)结构层次,有效地减轻了管理员授权的负担,提高了授权管理的效率;2)语义意义,能够与现实生活中的概念相关联,增强了角色的可解释性。最后,通过实验验证了该算法的正确性和有效性。
中图分类号:
[1]SANDHU R S,COYNE E J,FEINSTEINH L,et al.Role-based access control models[J].Computer,1996,29(2):38-47. [2]COYNE E J.Role engineering[C]∥Proceedings of the first ACM Workshop on Role-based access control.ACM,1996. [3]MITRA B,SURAL S,VAIDYA J,et al.A survey of role mining[J].ACM Computing Surveys (CSUR),2016,48(4):1-37. [4]SCHLEGELMILCH J,STEFFENS U.Role mining with ORCA[C]∥Proceedings of the tenth ACM symposium on Access control Models and Technologies.ACM,2005:168-176. [5]ZHANG D N,RAMAMOHANARAO K,EBRINGER T.Roleengineering using graph optimization[C]∥Proceedings of the 12th ACM Symposium on Access Control Models and Technologies.2007:139-144. [6]GUO Q,VAIDYA J,ATLURI V.The role hierarchy miningproblem:discovery of optimal role hierarchies[C]∥Computer Security Applications Conference.IEEE,2008:237-246. [7]SARMAH A K,HAZARIKA S M,SINHA S K.Formal concept analysis:current trends and directions[J].Artificial Intelligence Review,2015,44(1):47-86. [8]MOLLOY I,CHEN H,LI T,et al.Mining roles with multiple objectives[J].ACM Transactions on Information and System Security (TISSEC),2010,13(4):1-35. [9]SOBIESKI S,ZIELINSKI B.Modelling role hierarchy structure using the Formal Concept Analysis[J].Annales Umcs Informa-tica,2010,10(2):143-159. [10]KUMAR C.Designing role-based access control using formalconcept analysis[J].Security and Communication Networks,2013,6(3):373-383. [11]KUMAR C A,MOULISWARAN S C,LI J,et al.Role based access control design using triadic concept analysis[J].Journal of Central South University,2016,23(12):3183-3191. [12]ZHANG L,ZHANG H L,HAN D J,et al.Theory and Algorithm for Roles Minimization Problem in RBAC Based on Concept Lattice[J].Acta Electronica Sinica,2014,42(12):2371-2378.(in Chinese) 张磊,张宏莉,韩道军,等.基于概念格的 RBAC 模型中角色最小化问题的理论与算法[J].电子学报,2014,42(12):2371-2378. [13]GANTER B,WILLE R.Formal concept analysis:mathematical foundations[M].New York:Springer Science & Business Media,2012. [14]ZHI H L.Extended Model of Formal Concept Analysis Oriented for Heterogeneous Data Analysis[J].Acta Electronica Sinica,2013,41(12):2451-2455.(in Chinese) 智慧来.面向异构数据分析的形式概念分析扩展模型[J].电子学报,2013,41(12):2451-2455. [15]GODIN R,MINEAU G,MISSAOUI R,et al.Méthodes de classification conceptuelle basées sur les treillis de Galois et applications[J].Revued’Intelligence Artificielle,1995,9:105-137. [16]GANTER B.Two Basic Algorithms in Concept Analysis[C]∥International Conference on Formal Concept Analysis.Springer-Verlag,2010:312-340. |
[1] | 曹晓雯, 梁美玉, 鲁康康. 基于细粒度语义推理的跨媒体双路对抗哈希学习模型 Fine-grained Semantic Reasoning Based Cross-media Dual-way Adversarial Hashing Learning Model 计算机科学, 2022, 49(9): 123-131. https://doi.org/10.11896/jsjkx.220600011 |
[2] | 李瑶, 李涛, 李埼钒, 梁家瑞, Ibegbu Nnamdi JULIAN, 陈俊杰, 郭浩. 基于多尺度的稀疏脑功能超网络构建及多特征融合分类研究 Construction and Multi-feature Fusion Classification Research Based on Multi-scale Sparse Brain Functional Hyper-network 计算机科学, 2022, 49(8): 257-266. https://doi.org/10.11896/jsjkx.210600094 |
[3] | 陈晶, 吴玲玲. 多源异构环境下的车联网大数据混合属性特征检测方法 Mixed Attribute Feature Detection Method of Internet of Vehicles Big Datain Multi-source Heterogeneous Environment 计算机科学, 2022, 49(8): 108-112. https://doi.org/10.11896/jsjkx.220300273 |
[4] | 闫佳丹, 贾彩燕. 基于双图神经网络信息融合的文本分类方法 Text Classification Method Based on Information Fusion of Dual-graph Neural Network 计算机科学, 2022, 49(8): 230-236. https://doi.org/10.11896/jsjkx.210600042 |
[5] | 姜胜腾, 张亦弛, 罗鹏, 刘月玲, 曹阔, 赵海涛, 魏急波. 语义通信系统的性能度量指标分析 Analysis of Performance Metrics of Semantic Communication Systems 计算机科学, 2022, 49(7): 236-241. https://doi.org/10.11896/jsjkx.211200071 |
[6] | 曾志贤, 曹建军, 翁年凤, 蒋国权, 徐滨. 基于注意力机制的细粒度语义关联视频-文本跨模态实体分辨 Fine-grained Semantic Association Video-Text Cross-modal Entity Resolution Based on Attention Mechanism 计算机科学, 2022, 49(7): 106-112. https://doi.org/10.11896/jsjkx.210500224 |
[7] | 程成, 降爱莲. 基于多路径特征提取的实时语义分割方法 Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction 计算机科学, 2022, 49(7): 120-126. https://doi.org/10.11896/jsjkx.210500157 |
[8] | 林夕, 陈孜卓, 王中卿. 基于不平衡数据与集成学习的属性级情感分类 Aspect-level Sentiment Classification Based on Imbalanced Data and Ensemble Learning 计算机科学, 2022, 49(6A): 144-149. https://doi.org/10.11896/jsjkx.210500205 |
[9] | 郭亮, 杨兴耀, 于炯, 韩晨, 黄仲浩. 基于注意力机制和门控网络相结合的混合推荐系统 Hybrid Recommender System Based on Attention Mechanisms and Gating Network 计算机科学, 2022, 49(6): 158-164. https://doi.org/10.11896/jsjkx.210500013 |
[10] | 胡伏原, 万新军, 沈鸣飞, 徐江浪, 姚睿, 陶重犇. 深度卷积神经网络图像实例分割方法研究进展 Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network 计算机科学, 2022, 49(5): 10-24. https://doi.org/10.11896/jsjkx.210200038 |
[11] | 韩红旗, 冉亚鑫, 张运良, 桂婕, 高雄, 易梦琳. 基于共同子空间分类学习的跨媒体检索研究 Study on Cross-media Information Retrieval Based on Common Subspace Classification Learning 计算机科学, 2022, 49(5): 33-42. https://doi.org/10.11896/jsjkx.210200157 |
[12] | 王子茵, 李磊军, 米据生, 李美争, 解滨. 基于误分代价的变精度模糊粗糙集属性约简 Attribute Reduction of Variable Precision Fuzzy Rough Set Based on Misclassification Cost 计算机科学, 2022, 49(4): 161-167. https://doi.org/10.11896/jsjkx.210500211 |
[13] | 王志成, 高灿, 邢金明. 一种基于正域的三支近似约简 Three-way Approximate Reduction Based on Positive Region 计算机科学, 2022, 49(4): 168-173. https://doi.org/10.11896/jsjkx.210500067 |
[14] | 杨晓宇, 殷康宁, 候少麒, 杜文仪, 殷光强. 基于特征定位与融合的行人重识别算法 Person Re-identification Based on Feature Location and Fusion 计算机科学, 2022, 49(3): 170-178. https://doi.org/10.11896/jsjkx.210100132 |
[15] | 邓维斌, 朱坤, 李云波, 胡峰. FMNN:融合多神经网络的文本分类模型 FMNN:Text Classification Model Fused with Multiple Neural Networks 计算机科学, 2022, 49(3): 281-287. https://doi.org/10.11896/jsjkx.210200090 |
|