POSTER: Data Leakage Detection for Health Information System based on Memory Introspection

Sanoop Mallissery, Min Chieh Wu, Chun An Bau, Guan Zhang Huang, Chen Yu Yang, Wei Chun Lin, Yu Sung Wu*

*此作品的通信作者

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

The abundance of highly sensitive personal information in the Health Information System (HIS) has made it a prime target of data breach attacks. However, securing the system with existing Data Leakage Prevention (DLP) solutions is difficult due to a lack of security perimeter and diverse composition of software components. We propose the use of hypervisor-based memory introspection for implementing data leakage detection in such an environment. The approach looks for the presence of sensitive raw data in the memory of both the client machines and the server machines, transcending the dependence of pre-existing security perimeters. It is inherently compatible with different types of application software and robust against transport or at-rest data encryption. A prototype has been built on the Bareflank hypervisor and the OpenEMR platform. The evaluation results confirmed the effectiveness of the approach.

原文English
主出版物標題Proceedings of the 15th ACM Asia Conference on Computer and Communications Security, ASIA CCS 2020
發行者Association for Computing Machinery, Inc
頁面898-900
頁數3
ISBN(電子)9781450367509
DOIs
出版狀態Published - 5 10月 2020
事件15th ACM Asia Conference on Computer and Communications Security, ASIA CCS 2020 - Virtual, Online, Taiwan
持續時間: 5 10月 20209 10月 2020

出版系列

名字Proceedings of the 15th ACM Asia Conference on Computer and Communications Security, ASIA CCS 2020

Conference

Conference15th ACM Asia Conference on Computer and Communications Security, ASIA CCS 2020
國家/地區Taiwan
城市Virtual, Online
期間5/10/209/10/20

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