CICI: RSARC: Infrastructure Support for Securing Large-Scale Scientific Workflows
CICI: RSARC: Infrastructure Support for Securing Large-Scale Scientific Workflows
批准号:
1738929
负责人:
Ping Yang
金额:
$100.0万
依托单位:
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
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The scientific workflow is an important paradigm for automating and accelerating data processing and sharing in the scientific community. The correctness of scientific discoveries relies on the trustworthiness and reliability of the data processed by scientific workflows and the underlying cyberinfrastructure. Unfortunately, modern scientific workflow systems lack robust infrastructure support for the trustworthy execution of scientific workflows and for the protection of the data processed by such workflows. A scientist or student may forge or alter datasets or computation simply to get papers accepted for publication. A malicious user may also publish forged workflow data on websites, misleading other scientists into investigating and publishing invalid results. This project aims to support a community of engineers and scientists to collaboratively and securely collect, analyze, and share data using scientific workflows. The success of this project contributes significantly to the national cyberinfrastructure vision of securing the scientific discovery process for a wide range of science and engineering disciplines.This project develops infrastructure support for secure execution of scientific workflows, detection of anomalous execution flows, and protection of scientific data. In particular, this project: (1) develops a trusted execution environment for scientific workflows leveraging the Intel Software Guard Extension (SGX) to protect the execution of scientific workflows as well as the data processed by scientific workflows; (2) produces encrypted, tamper-proof, and non-repudiable block-graphs that enable scientists to verify the origin of scientific data and examine how a piece of data was modified and distributed; and (3) develops a machine-learning based anomaly detection technique to detect anomalous execution flows based on logs collected by the underlying cyberinfrastructure.
期刊论文(18)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
DOI:
10.1109/tsc.2019.2921586
发表时间:
2022-01-01
期刊:
IEEE TRANSACTIONS ON SERVICES COMPUTING
影响因子:
8.1
作者:
[Bhuyan, Fahima Amin, Lu, Shiyong, Ahmed, Ishtiaq]
通讯作者:
Ahmed, Ishtiaq
Deep-Learning-as-a-Workflow (DLaaW): An Innovative Approach to Enabling Deep Learning in Scientific Workflows
深度学习作为工作流程 (DLaaW):在科学工作流程中启用深度学习的创新方法
DOI:
10.1109/bigdata52589.2021.9671626
发表时间:
2021
期刊:
IEEE International Conference on Big Data
影响因子:
--
作者:
[Liu, Junwen, Xiao, Ziyun, Lu, Shiyong, Che, Dunren]
通讯作者:
Che, Dunren
DOI:
10.1109/sec.2018.00057
发表时间:
2018-10
期刊:
2018 IEEE/ACM Symposium on Edge Computing (SEC)
影响因子:
--
作者:
[Zhenyu Ning;Jinghui Liao;Fengwei Zhang;Weisong Shi]
通讯作者:
Zhenyu Ning;Jinghui Liao;Fengwei Zhang;Weisong Shi
DOI:
10.1109/scc49832.2020.00023
发表时间:
2020-11
期刊:
2020 IEEE International Conference on Services Computing (SCC)
影响因子:
--
作者:
[Ishtiaq Ahmed;S. Mofrad;Shiyong Lu;Changxin Bai;Fengwei Zhang;D. Che]
通讯作者:
Ishtiaq Ahmed;S. Mofrad;Shiyong Lu;Changxin Bai;Fengwei Zhang;D. Che
DOI:
10.1109/dsn53405.2022.00028
发表时间:
2022-06
期刊:
2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)
影响因子:
--
作者:
[J. D. Herath;Priti Wakodikar;Pin Yang;Guanhua Yan]
通讯作者:
J. D. Herath;Priti Wakodikar;Pin Yang;Guanhua Yan
共 16 条
CyberCorps Scholarship for Service: Expanding and Strengthening the National Cybersecurity Workforce
-
批准号:2146212
-
项目类别:Continuing Grant
-
资助金额:$352.04万
-
财政年份:2022
-
负责人:Ping Yang
-
依托单位:
EAGER: Develop Robust Light-Scattering Computational Capability Based on the Method of Separation of Variables in Spheroidal Coordinates for Small-to-Large Spheroids
-
批准号:2153239
-
项目类别:Standard Grant
-
资助金额:$19.96万
-
财政年份:2021
-
负责人:Ping Yang
-
依托单位:
Development of Community Light Scattering Computational Capabilities
-
批准号:1826936
-
项目类别:Continuing Grant
-
资助金额:$59.39万
-
财政年份:2018
-
负责人:Ping Yang
-
依托单位:
Collaborative Research: Systematic Evaluation and Further Improvement of Present Broadband Radiative Transfer Modeling Capabilities
-
批准号:1632209
-
项目类别:Standard Grant
-
资助金额:$50.94万
-
财政年份:2016
-
负责人:Ping Yang
-
依托单位:
Collaborative Research: Inferring Marine Particle Properties from Polarized Volume Scattering Functions
-
批准号:1459180
-
项目类别:Standard Grant
-
资助金额:$19.71万
-
财政年份:2015
-
负责人:Ping Yang
-
依托单位:
Development of Rigorous Computational Capabilities Based on the Invariant Imbedding Principle for the Simulation of the Optical Properties of Dust and Ice Crystals
-
批准号:1338440
-
项目类别:Standard Grant
-
资助金额:$56.54万
-
财政年份:2013
-
负责人:Ping Yang
-
依托单位:
Study Dust Optical and Radiative Properties Using Optimal Morphological Sets
-
批准号:0803779
-
项目类别:Continuing Grant
-
资助金额:$41.99万
-
财政年份:2008
-
负责人:Ping Yang
-
依托单位:
CAREER: Investigation of the Scattering and Radiative Properties of Ice and Mixed-Phase Clouds
-
批准号:0239605
-
项目类别:Continuing Grant
-
资助金额:$62.34万
-
财政年份:2003
-
负责人:Ping Yang
-
依托单位:
海外基金