健康信息系统中使用主题模型的隐私感知风险自适应访问控制

Wenxi Zhang, Hao Li, Min Zhang, Zhiquan Lv
{"title":"健康信息系统中使用主题模型的隐私感知风险自适应访问控制","authors":"Wenxi Zhang, Hao Li, Min Zhang, Zhiquan Lv","doi":"10.1145/3205977.3205991","DOIUrl":null,"url":null,"abstract":"Traditional role-based access control fails to meet the privacy requirements for patient data in medical systems, as it is infeasible for policy makers to foresee what information doctors may need for diagnosis and treatment in various situations. The universal practice in hospitals is to grant doctors unlimited access, which in turn increases the risk of breaching patient privacy. In this paper, we propose a dynamic risk-adaptive access control model for health IT systems by taking into consideration the relationships between data and access behaviors. By training topic models to portray individual and group-level access behaviors, we quantify the risk for each user over a certain period of time. Malicious users are supposed to get higher risk scores than honest users due to improper requests. Thus their further access would be denied under our access control scheme. The topic model and risk scores are periodically updated to advance the self-adaptability of the system. Experimental results have shown that our solution could effectively distinguish malicious doctors even if they deliberately conceal the misconducts.","PeriodicalId":423087,"journal":{"name":"Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Privacy-Aware Risk-Adaptive Access Control in Health Information Systems using Topic Models\",\"authors\":\"Wenxi Zhang, Hao Li, Min Zhang, Zhiquan Lv\",\"doi\":\"10.1145/3205977.3205991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional role-based access control fails to meet the privacy requirements for patient data in medical systems, as it is infeasible for policy makers to foresee what information doctors may need for diagnosis and treatment in various situations. The universal practice in hospitals is to grant doctors unlimited access, which in turn increases the risk of breaching patient privacy. In this paper, we propose a dynamic risk-adaptive access control model for health IT systems by taking into consideration the relationships between data and access behaviors. By training topic models to portray individual and group-level access behaviors, we quantify the risk for each user over a certain period of time. Malicious users are supposed to get higher risk scores than honest users due to improper requests. Thus their further access would be denied under our access control scheme. The topic model and risk scores are periodically updated to advance the self-adaptability of the system. Experimental results have shown that our solution could effectively distinguish malicious doctors even if they deliberately conceal the misconducts.\",\"PeriodicalId\":423087,\"journal\":{\"name\":\"Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3205977.3205991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23nd ACM on Symposium on Access Control Models and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3205977.3205991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

传统的基于角色的访问控制无法满足医疗系统中对患者数据的隐私要求,因为决策者无法预见医生在各种情况下的诊断和治疗可能需要哪些信息。医院的普遍做法是给予医生无限制的访问权限,这反过来又增加了侵犯患者隐私的风险。在本文中,我们提出了一种考虑数据和访问行为之间关系的健康IT系统动态风险自适应访问控制模型。通过训练主题模型来描绘个人和群体级别的访问行为,我们量化了每个用户在特定时间段内的风险。恶意用户由于不正当的请求,应该比诚实用户获得更高的风险评分。因此,在我们的访问控制方案下,他们的进一步访问将被拒绝。定期更新主题模型和风险评分,提高系统的自适应性。实验结果表明,我们的解决方案可以有效地识别恶意医生,即使他们故意隐瞒不当行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Privacy-Aware Risk-Adaptive Access Control in Health Information Systems using Topic Models
Traditional role-based access control fails to meet the privacy requirements for patient data in medical systems, as it is infeasible for policy makers to foresee what information doctors may need for diagnosis and treatment in various situations. The universal practice in hospitals is to grant doctors unlimited access, which in turn increases the risk of breaching patient privacy. In this paper, we propose a dynamic risk-adaptive access control model for health IT systems by taking into consideration the relationships between data and access behaviors. By training topic models to portray individual and group-level access behaviors, we quantify the risk for each user over a certain period of time. Malicious users are supposed to get higher risk scores than honest users due to improper requests. Thus their further access would be denied under our access control scheme. The topic model and risk scores are periodically updated to advance the self-adaptability of the system. Experimental results have shown that our solution could effectively distinguish malicious doctors even if they deliberately conceal the misconducts.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Parametric RBAC Maintenance via Max-SAT Sensing or Watching?: Balancing Utility and Privacy in Sensing Systems via Collection and Enforcement Mechanisms Privacy-Aware Risk-Adaptive Access Control in Health Information Systems using Topic Models Network Policy Enforcement Using Transactions: The NEUTRON Approach Access Control Enforcement within MQTT-based Internet of Things Ecosystems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1