Collaborative Research: CyberTraining: Implementation: Medium: Cross-Disciplinary Training for Joint Cyber-Physical Systems and IoT Security
Collaborative Research: CyberTraining: Implementation: Medium: Cross-Disciplinary Training for Joint Cyber-Physical Systems and IoT Security
批准号:
2230086
负责人:
Elias Bou-Harb
金额:
$59.95万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-01 至 2023-12-31
中文摘要
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英文摘要
Critical infrastructures, such as the power grid, water systems, and manufacturing plants, continue to be targeted by stealthy and debilitating cyber and physical attacks. These attacks not only hinder our national security but also jeopardize our economic prosperity. Several hurdles impede addressing the security of such critical assets, including the integration of new possibly vulnerable sensing technologies deep within such realms, in addition to the profound lack of relevant training experts from academia and both private and public sectors. Along the same line of thought, the shortage of empirical data originating from such realms, in conjunction with the complexity of such systems, further exposes the problem when facing the challenges of sophisticated state-sponsored attackers. To this end, this project serves NSF's mission to promote the progress of science by offering well-rounded training to research scientists coming from diverse related areas. The project puts forward multidisciplinary curricula in addition to catalyzing critical infrastructure training and research, while establishing active and actionable dissemination partnerships with numerous stakeholders, tangibly influencing the security of such interrelated, highly-important societal systems. The project also widely influences the training of women and minorities in these imperative cross-disciplinary areas across the US. The project uniquely curates contextualized, large-scale benign and malicious cyber and cyber-physical empirical data from real infrastructure systems to strongly enable hands-on training and research. The project then develops automated methodologies to annotate such data while indexing and sharing it with relevant research scientists to empower forward-looking research workforce development. The project also designs, delivers and integrates cross-disciplinary curricula, composed of undergraduate and graduate courses and a certificate program, dealing with evolving topics such as, physical modeling of system dynamics, related empirically driven data science applications, and joint operational security analytics. It also offers unique training opportunities with relevant private and public sector partners for both pre- and post-graduation trainees, rendered by capstone projects, internships, and competitive placement options. The project also designs and implements various security techniques, along with realistic emulation and simulation toolsets, to offer practical training expertise to researchers. The project utilizes virtualized lab setups to offer self-paced training of such developed training material, while achieving considerable outreach to relevant researchers across the US and beyond. The project fosters a community of impactful experts in the critical infrastructure security area to widely-disseminate such developed training materials and labs through coordinating and hosting yearly workshops at the collaborating institutions. The project is steered by an established program evaluation body that is composed of leading NSF Industry-University Research Partnership experts, pedagogy facilitators, and representative researchers from operational local and national training and research centers. This project is jointly funded by OAC and the CyberCorps program.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.
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Collaborative Research: CyberTraining: Implementation: Medium: Cross-Disciplinary Training for Joint Cyber-Physical Systems and IoT Security
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批准号:2404946
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项目类别:Continuing Grant
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资助金额:$59.95万
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财政年份:2023
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负责人:Elias Bou-Harb
-
依托单位:
OAC Core: Data-driven Methods and Techniques For Protecting Research and Critical Cyberinfrastructure By Characterizing and Defending Against Ransomware
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批准号:2348719
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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:2023
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负责人:Elias Bou-Harb
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依托单位:
OAC Core: Data-driven Methods and Techniques For Protecting Research and Critical Cyberinfrastructure By Characterizing and Defending Against Ransomware
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批准号:2104273
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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:2021
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负责人:Elias Bou-Harb
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依托单位:
CRII: OAC: Inferring, Attributing, Mitigating and Analyzing the Malicious Orchestration of Internet-scale Exploited IoT Devices: A Network Telescope Approach
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批准号:1953050
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项目类别:Standard Grant
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资助金额:$11.18万
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财政年份:2019
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负责人:Elias Bou-Harb
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依托单位:
OAC Core: Small: Devising Data-driven Methodologies by Employing Large-scale Empirical Data to Fingerprint, Attribute, Remediate and Analyze Internet-scale IoT Maliciousness
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批准号:1907821
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项目类别:Standard Grant
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资助金额:$49.69万
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财政年份:2019
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负责人:Elias Bou-Harb
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依托单位:
CRII: OAC: Inferring, Attributing, Mitigating and Analyzing the Malicious Orchestration of Internet-scale Exploited IoT Devices: A Network Telescope Approach
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批准号:1755179
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项目类别:Standard Grant
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资助金额:$17.5万
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财政年份:2018
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负责人:Elias Bou-Harb
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依托单位:
国内基金
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