Research Initiation Award: Towards Realizing a Self-Protecting Healthcare Information System for the Internet of Medical Things

研究启动奖：实现医疗物联网自我保护医疗信息系统

• 批准号: 1700391
• 负责人: Qian Chen
• 金额: $ 30万
• 依托单位: Savannah State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-15 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1700391&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Towards; Realizing

Research Initiation Awards provide support for faculty at Historically Black Colleges and Universities who are building a research program. It is expected that the award helps to further the faculty member's research capability and effectiveness, improves research and teaching at her home institution, and involves undergraduate students in research experiences. The award to Savannah State University has potential broader and societal impact in a number of areas. The project seeks to develop an autonomic security management framework and apply the framework to realize a self-protecting Healthcare Information System (HIS). The comprehensive self-protection system will enable HISs to autonomously assess their potential security risks, initiate prevention mechanisms, detect realtime intrusions and react to cyber attacks, thus maintaining normal performance and enhancing patient data security and privacy. Undergraduate students will gain research experiences and the research will be integrated in a number of cyber security courses.The research seeks to adopt computing technology to realize a Self-Protecting Healthcare Information System (SPHIS) that can autonomously assess system security risks, initiate prevention mechanisms, detect real-time intrusions and react to cyber attacks with little or no human intervention. Eventually the SPHIS will maintain the Internet of Medical Things (IoMT) ecosystem's normal performance and enhance patients' data security and privacy. An Internet of Things cyber security lab and Healthcare Information System cloud testbed will be built to validate the SPHIS autonomous feature and functions using real-world cyber attacks. The research will determine cyber attacks and use time series forecasting methods to initialize early warning modules and send attack alerts based on the variation of power utilization of IoMT devices. Power consumption of IoMT devices thus will be collected offline when the system is under normal and known cyber attack situations. The power data will be used to set up the IoMT ecosystem's normal behavior region by data mining techniques, and help to identify abnormal behaviors and detect cyber attacks using unsupervised learning techniques. The power data of IoMT devices will be collected online when the HIS is compromised by unknown attacks, and the power data will be analyzed by a network of forensics analysis tools. The attack patterns will be added to update the intrusion detection module. A dynamic intrusion response system will be developed to select the optimal prevention and protection mechanisms for mitigating cyber attacks. The research promises to change the current HIS cyber security state from poorly prepared to well defended against emerging cyber attacks. This research will also contribute to development of the cyber security workforce and enhance security awareness in healthcare organizations.

研究启动奖为历史上黑人学院和大学正在建立研究项目的教师提供支持。预计该奖项有助于提高教师的研究能力和效率，改善其所在机构的研究和教学，并让本科生参与研究经验。萨凡纳州立大学的这一奖项在许多领域都具有潜在的更广泛的社会影响。该项目旨在开发一个自主安全管理框架，并应用该框架来实现自我保护的医疗信息系统（HIS）。全面的自我保护系统将使HIS能够自主评估潜在的安全风险，启动预防机制，检测实时入侵并对网络攻击做出反应，从而保持正常性能并增强患者数据的安全和隐私。本科生将获得研究经验，研究成果将整合到多个网络安全课程中。该研究旨在采用计算技术实现自我保护的医疗信息系统（SPHIS），能够自主评估系统安全风险，启动预防机制，检测实时入侵并对网络攻击做出反应，几乎不需要人为干预。最终SPHIS将维持医疗物联网（IoMT）生态系统的正常性能并增强患者的数据安全和隐私。将建立一个物联网网络安全实验室和医疗信息系统云测试平台，以使用真实世界的网络攻击来验证 SPHIS 的自主特性和功能。该研究将确定网络攻击，并使用时间序列预测方法来初始化预警模块，并根据物联网设备的电力利用率的变化发送攻击警报。因此，当系统处于正常且已知的网络攻击情况下时，将离线收集 IoMT 设备的功耗。电力数据将用于通过数据挖掘技术建立物联网生态系统的正常行为区域，并利用无监督学习技术帮助识别异常行为和检测网络攻击。当HIS受到未知攻击时，IoMT设备的电力数据将被在线收集，并且电力数据将通过取证分析工具网络进行分析。将添加攻击模式以更新入侵检测模块。 将开发动态入侵响应系统，以选择最佳的预防和保护机制来减轻网络攻击。该研究有望将当前的 HIS 网络安全状态从准备不足转变为对新兴网络攻击做好防御。这项研究还将有助于网络安全劳动力的发展并提高医疗机构的安全意识。