| Android平台下细粒度权限管理机制设计与实现 |
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| 引用本文： | 孙 岚,李永忠.Android平台下细粒度权限管理机制设计与实现[J].教育技术导刊,2019,18(8):131-135. |
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| 作者姓名： | 孙 岚 李永忠 |
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| 作者单位： | 江苏科技大学 计算机学院，江苏 镇江 212003 |
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| 摘 要： | 针对Android平台粗粒度权限管理机制的漏洞，提出一种细粒度权限管理机制。该方案实现了恶意软件识别、隐私权限分析与警告，以及权限选择与修改功能。其中恶意权限识别功能中采用了卡方检验法、聚类算法及改进的朴素贝叶斯算法。运用该系统对1 000个样本进行实验，得出恶意软件误判率约为9.75%，检测准确率约为90.25%。实验结果表明，该方案使普通用户在面对各种应用时能更合理地授予及修改权限，从而大幅降低了Android平台下权限控制的危险性。
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| 关 键 词： | Android 细粒度权限管理机制 权限控制 恶意权限检测 |
| 收稿时间： | 2018-11-27 |
Design and Implementation of Fine-grained Rights Management Mechanism under Android Platform |
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| SUN Lan,LI Yong-zhong.Design and Implementation of Fine-grained Rights Management Mechanism under Android Platform[J].Introduction of Educational Technology,2019,18(8):131-135. |
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| Authors: | SUN Lan LI Yong-zhong |
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| Institution: | School of Computer， Jiangsu University of Science and Technology， Zhenjiang 212003， China |
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| Abstract: | In order to solve the problem of the coarse-grained permissions management system of the Android platform， this paper proposes a fine-grained permissions management system. This program implements many functions， including identification of malware， analysis of privacy permissions， selection and modification of permissions. Chi-square test， clustering algorithm and improved naive Bayesian algorithm are adopted by malicious identification function. This system was used to conduct experiments on 1000 samples， the false positive rate of malware was about 9.75%， and the detection accuracy was about 90.25%. Experiment result have shown that the control of privacy-related permissions is more secure and reliable， so that this solution allows ordinary users to grant and modify permissions more reasonably when faced with various applications， greatly reducing the risk of permission control under the Android platform. |
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| Keywords: | Android fine-grained permissions management system permission control malicious permission detection |
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