CICI: RSARC: SECTOR: Building a Secure and Compliant Cyberinfrastructure for Translational Research

CICI：RSARC：部门：为转化研究构建安全且合规的网络基础设施

• 批准号: 1738965
• 负责人: Yan Luo
• 金额: $ 99.97万
• 依托单位: University of Massachusetts Lowell
• 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: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1738965&HistoricalAwards=false
• 关键词: CICI; RSARC; SECTOR; Building; Secure

Translational research has been driven by the increasing amount of heterogeneous data sets collected from medical instruments, sensors, patient diagnosis records, genomic and microbiome samples. The recent advancement in information technology greatly accelerates the innovation in translational research by applying in-depth analysis on these data with large scale computing and storage resources. Clinical researchers now heavily rely on such cyberinfrastructure to understand trends, derive correlations, and/or identify anomalies, which are instrumental to accurate diagnosis, precision drug discovery and effective treatment of diseases. In this context, the security of the patient data, the efficient sharing of data, and the processing of data in a regulation compliant fashion are critical. This project addresses the resource limitations and security aspects of data-driven translational research. The project will greatly speed up clinical research activities that rely heavily on the analysis of sensitive data. The resulting software defined security infrastructure can be applied to a wide range of cyberinfrastructure that carries sensitive data. The project will strengthen the collaboration among computer scientists, clinical researchers, IT managers and provides a rare opportunity to address the cyberinfrastructure challenges in a holistic way instead of an ad hoc, incremental manner.This project designs and deploys a Security and compliant Cyberinfrastructure for Translational Research (SECTOR) that enables sharing and computing on sensitive data sets between private compute clusters, a shared HPC facility and/or a HIPAA compliant cloud. Specifically, it (1) leverages the emerging software defined infrastructure (SDI), blockchain and secure domain name system to extend the boundary of computing on sensitive and private data. This is the first project to bring the agility and resilience of SDI to clinical research activities; (2) designs a framework that enables the deployment of a new workflows with fine grained user and access control that are compliant with the HIPAA (Health Insurance Portability and Accountability Act of 1996) technical safeguard; (3) enables the migration of data computation using streaming based data redirection and processing, requiring very little effort in porting existing scientific applications; (4) designs a portal that exploits the underlying SDI resources to help various stakeholders to express their workflow and simplify the management of healthcare resources.

从医疗仪器、传感器、患者诊断记录、基因组和微生物组样本中收集的异质数据集越来越多，这推动了转化研究。近年来信息技术的发展通过利用大规模计算和存储资源对这些数据进行深入分析，大大加速了转化研究的创新。临床研究人员现在严重依赖此类网络基础设施来了解趋势、推导相关性和/或识别异常，这有助于准确诊断、精确药物发现和有效治疗疾病。 在这种情况下，患者数据的安全性、数据的有效共享以及以符合法规的方式处理数据至关重要。该项目解决了数据驱动的转化研究的资源限制和安全问题。该项目将大大加快严重依赖敏感数据分析的临床研究活动。由此产生的软件定义的安全基础设施可以应用于各种携带敏感数据的网络基础设施。该项目将加强计算机科学家、临床研究人员、IT管理人员之间的合作，并提供一个难得的机会，以整体的方式而不是临时的、渐进的方式来解决网络基础设施的挑战。该项目设计和部署了一个安全和合规的转化研究网络基础设施（SECTOR），使私有计算集群之间能够共享和计算敏感数据集，共享HPC设施和/或符合HIPAA的云。具体而言，它（1）利用新兴的软件定义基础设施（SDI），区块链和安全域名系统来扩展敏感和私有数据的计算边界。这是第一个将SDI的敏捷性和弹性引入临床研究活动的项目;（2）设计了一个框架，该框架能够部署具有细粒度用户和访问控制的新工作流程，这些工作流程符合HIPAA（1996年《健康保险携带和责任法》）技术保障;（3）使得能够使用基于流的数据重定向和处理来迁移数据计算，在移植现有的科学应用方面需要非常少的努力;（4）设计一个门户网站，利用基础SDI资源，帮助不同的利益相关者表达他们的工作流程，简化医疗资源的管理。

项目成果

A Spatio-temporal Learning for Music Conditioned Dance Generation

• DOI: 10.1145/3536221.3556618
• 发表时间: 2022-11
• 期刊: Proceedings of the 2022 International Conference on Multimodal Interaction
• 作者: Li Zhou;Yan Luo

CareNet: Building a Secure Software-defined Infrastructure for Home-based Healthcare

CareNet：为家庭医疗保健构建安全的软件定义基础设施

• DOI: 10.1145/3040992.3041007
• 发表时间: 2017
• 期刊: SDN-NFVSec '17 Proceedings of the ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization
• 作者: Li, Peilong;Xu, Chen;Luo, Yan;Cao, Yu;Mathew, Jomol;Ma, Yunsheng
• 通讯作者: Ma, Yunsheng

TLS Encrypted Application Classification Using Machine Learning with Flow Feature Engineering

使用机器学习和流特征工程进行 TLS 加密应用程序分类

• DOI: 10.1145/3442520.3442529
• 发表时间: 2020
• 期刊: ICCNS 2020: 2020 the 10th International Conference on Communication and Network Security
• 作者: Barut, Onur;Zhu, Rebecca;Luo, Yan;Zhang, Tong
• 通讯作者: Zhang, Tong

CareNet: Building Regulation-Compliant Home-Based Healthcare Services with Software-Defined Infrastructure

• DOI: 10.1109/chase.2017.121
• 发表时间: 2017-07
• 期刊: 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
• 作者: Peilong Li;Chen Xu;Yan Luo;Yu Cao;J. Mathew;Yunsheng Ma

A-HRNet: Attention Based High Resolution Network for Human pose estimation

• DOI: 10.1109/transai49837.2020.00016
• 发表时间: 2020-09
• 期刊: 2020 Second International Conference on Transdisciplinary AI (TransAI)
• 作者: Ying Li;Chenxi Wang;Yu Cao;Benyuan Liu;Yan Luo;Honggang Zhang