Collaborative Research: PPoSS: Planning:S3-IoT: Design and Deployment of Scalable, Secure, and Smart Mission-Critical IoT Systems
Collaborative Research: PPoSS: Planning:S3-IoT: Design and Deployment of Scalable, Secure, and Smart Mission-Critical IoT Systems
批准号:
2028740
负责人:
Fanxin Kong
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2022-09-30
中文摘要
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英文摘要
The growing capabilities of sensing, computing and communication devices are leading to an explosion of Internet of Things (IoT) infrastructures. In the meantime, advances in technologies such as autonomous systems and artificial intelligence promise enormous economic and societal benefits. Naturally, it is desirable to deploy these technologies in IoT infrastructures. However, such deployments present daunting changes for increasingly scaled-up IoT infrastructures in mission-critical applications such as medical, energy, transportation, and industrial-automation systems. These challenges stem from several major aspects in terms of scalability. First, the number of edge devices can be enormous, often in the order of billions, which makes centralized management infeasible. Second, there are multiple layers of heterogeneity. An IoT system can consist of heterogeneous computing subsystems; each subsystem can have heterogeneous computing devices; and each single device can be composed of different kinds of computing components. Third, mission-critical applications have stringent requirements in correctness, resilience, timeliness, security and safety. It is difficult for a large-scale IoT system to satisfy these requirements due to increasing opportunities for adversarial activity.To tackle these challenges, this project aims to develop a cross-layer and full hardware/software stack solution, referred to as the S3-IoT framework, for the design and deployment of scalable, secure, and smart mission-critical IoT systems. The S3-IoT framework will span three different computation layers, including data centers, gateways/aggregators, and edge devices, and cover four research foci, i.e., resource management, security and privacy, computer architecture/systems, and algorithms. In this planning project, an initial version of the S3-IoT framework will be developed. The S3-IoT framework will (i) leverage a layered structure - data centers, gateways/aggregators, and edge devices to accommodate the huge number of edge devices; (ii) develop cross-layer techniques to deal with the heterogeneity among these layers; and (iii) propose hardware and software co-design approaches that embrace the heterogeneity among computing components to improve the performance of all components within an individual layer. The S3-IoT framework will be evaluated by developing simulators with the layered structure as well as a small scale, comprehensive experimental testbed. The success of this planning project will lead to a convincing path to effective deployment of mission-critical IoT systems and infrastructures, particularly in terms of improving resilience to environmental uncertainties, system internal errors and faults, and malicious attacks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(7)
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DOI:
10.1145/3477010
发表时间:
2021-09
期刊:
ACM Transactions on Embedded Computing Systems (TECS)
影响因子:
--
作者:
[Lin Zhang;Pengyuan Lu;Fanxin Kong;Xin Chen;O. Sokolsky;Insup Lee]
通讯作者:
Lin Zhang;Pengyuan Lu;Fanxin Kong;Xin Chen;O. Sokolsky;Insup Lee
DOI:
10.1145/3489517.3530555
发表时间:
2022-07
期刊:
Proceedings of the 59th ACM/IEEE Design Automation Conference
影响因子:
--
作者:
[Lin Zhang;Zifan Wang;Mengyu Liu;Fanxin Kong]
通讯作者:
Lin Zhang;Zifan Wang;Mengyu Liu;Fanxin Kong
Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems
自主网络物理系统中的实时自适应传感器攻击检测
DOI:
10.1109/rtas52030.2021.00027
发表时间:
2021
期刊:
2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS
影响因子:
--
作者:
[Akowuah, Francis, Kong, Fanxin]
通讯作者:
Kong, Fanxin
DOI:
10.1109/rtss49844.2020.00028
发表时间:
2020-12
期刊:
2020 IEEE Real-Time Systems Symposium (RTSS)
影响因子:
--
作者:
[Lin Zhang;Xin Chen;Fanxin Kong;A. Cárdenas]
通讯作者:
Lin Zhang;Xin Chen;Fanxin Kong;A. Cárdenas
Recovery-by-Learning: Restoring Autonomous Cyber-physical Systems from Sensor Attacks
通过学习恢复:从传感器攻击中恢复自主网络物理系统
DOI:
10.1109/rtcsa52859.2021.00015
发表时间:
2021
期刊:
2021 IEEE 27th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA
影响因子:
--
作者:
[Akowuah, Francis, Prasad, Romesh, Espinoza, Carlos Omar, Kong, Fanxin]
通讯作者:
Kong, Fanxin
共 6 条
Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems
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批准号:2333980
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2023
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负责人:Fanxin Kong
-
依托单位:
Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems
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批准号:2143256
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2022
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负责人:Fanxin Kong
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依托单位:
EAGER: Techniques for Deploying Mission Critical IoT Applications
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批准号:1720579
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项目类别:Standard Grant
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资助金额:$28.57万
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财政年份:2017
-
负责人:Fanxin Kong
-
依托单位:
国内基金
海外基金
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