Collaborative Research: SFS Program: Strengthening the National Cyber Security Workforce
Collaborative Research: SFS Program: Strengthening the National Cyber Security Workforce
批准号:
1663350
负责人:
Fan Wu
金额:
$177.61万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-01-01 至 2024-12-31
中文摘要
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英文摘要
Data loss, cybercrimes, and security breaches have posed significant threats to cyberspace, and many experts expect that the number and severity of cyber-attacks will increase. The protection and security of computing systems, critical infrastructure, and cyberspace are vital to nearly all aspects of our society. To secure cyberspace, the nation needs capable, well-trained, and responsive professionals and experts in the cybersecurity workforce. The University of Tennessee at Chattanooga (UTC), in collaboration with the Tuskegee University (TU), launches a new Scholarship for Service (SFS) program to graduate highly capable and talented cybersecurity professionals with Master's degrees. Both UTC and TU host a Center of Academic Excellence in Information Assurance Education/Cyber Defense (CAE IA/CD), designated by the National Security Agency and the Department of Homeland Security. As such, both institutions are well equipped to prepare SFS scholars for cybersecurity careers in local, state, and federal governments. The proposed new SFS program recruits exceptional students through academic and community outreach initiatives. Strategies include recruiting from the Collegiate Cyber Defense Competition (CCDC) team, Honor College, and outreaching to other institutions. The SFS scholars will be selected based on a holistic consideration of credential ranking and group diversity. The SFS program will implement cohort programs, and students will gain common cohort experiences including: taking common curriculum in each cohort; attending monthly forums or field trips; conducting collaborative research; participating in security conferences; joining CCDC; and conducting K-12 outreach. These strong and well-designed academic programs, combined with high-quality student services, and paired with a network of industry partnerships, will help prepare quality professionals in cybersecurity. The SFS program will also assist scholars' transition into government through mentorship and career planning efforts. This project will strengthen the cybersecurity workforce by graduating well-trained cybersecurity professionals to defend the cyber-infrastructure, critical infrastructure, citizen privacy, and daily activities in cyberspace. The partnership between UTC and TU (a strong HBCU school) will help diversify the cybersecurity workforce. The knowledge and experiences gained through this program will be disseminated in regional and national conferences, workshops, and journals to inspire collaboration among institutions, government, and industry in creating and training highly capable cybersecurity professionals. Through outreach to local communities and K-12 schools, including those with large populations of underrepresented groups in computing, this project will promote awareness of the cybersecurity issues that the nation faces as well as disseminate basic knowledge about information security.
期刊论文(9)
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Authentic Learning Secure Software Development (SSD) in Computing Education
计算机教育中的真实学习安全软件开发(SSD)
DOI:
--
发表时间:
2018
期刊:
2018 IEEE Frontiers in Education Conference (FIE
影响因子:
--
作者:
[Qian, Kai, Lo, Dan, Parizi, Reza, Wu, Fan, Agu, Emmanuel, and Chu, Bei-Tseng]
通讯作者:
and Chu, Bei-Tseng
DOI:
10.1007/s11528-020-00502-7
发表时间:
2020-11
期刊:
TechTrends : for leaders in education & training
影响因子:
--
作者:
[Bhuyan J, Wu F, Thomas C, Koong K, Won Hur J, Wang CH]
通讯作者:
Wang CH
Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection
基于案例研究的网络安全量子机器学习方法:用于恶意软件分类和保护的量子支持向量机
DOI:
10.1109/compsac57700.2023.00161
发表时间:
2023
期刊:
and Applications Conference (COMPSAC
影响因子:
--
作者:
[Akter, Mst Shapna, Shahriar, Hossain, Iqbal Ahamed, Sheikh, Datta Gupta, Kishor, Rahman, Muhammad, Mohamed, Atef, Rahman, Mohammad, Rahman, Akond, Wu, Fan]
通讯作者:
Wu, Fan
Authentic Learning Approach for Artificial Intelligence Systems Security and Privacy
人工智能系统安全和隐私的真实学习方法
DOI:
10.1109/compsac57700.2023.00151
发表时间:
2023
期刊:
and Applications Conference (COMPSAC
影响因子:
--
作者:
[Akter, Mst Shapna, Shahriar, Hossain, Lo, Dan, Sakib, Nazmus, Qian, Kai, Whitman, Michael, Wu, Fan]
通讯作者:
Wu, Fan
DOI:
10.1109/compsac57700.2023.00284
发表时间:
2023-06
期刊:
2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)
影响因子:
--
作者:
[Md Mostafizur Rahman;Aiasha Siddika Arshi;Md. Golam Moula Mehedi Hasan;Sumayia Farzana Mishu;Hossain Shahriar-Hossain-Sh]
通讯作者:
Md Mostafizur Rahman;Aiasha Siddika Arshi;Md. Golam Moula Mehedi Hasan;Sumayia Farzana Mishu;Hossain Shahriar-Hossain-Sh
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国内基金
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