CyberCorps Scholarship for Service: Preparing Future Cybersecurity Professionals with Data Science Expertise

Cyber​​Corps 服务奖学金:为未来的网络安全专业人员提供数据科学专业知识

基本信息

  • 批准号:
    2142229
  • 负责人:
  • 金额:
    $ 406.26万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-02-01 至 2027-01-31
  • 项目状态:
    未结题

项目摘要

As increasingly sophisticated and varied cyberattacks become common, it is crucial that well-trained and agile cybersecurity professionals enter industry and government positions. These professionals should be adept at analyzing the enormous amounts of data generated by modern computing systems to facilitate processing at the scale and rates necessary to identify new attacks. The CyberCorps(R) Scholarship for Service (SFS) project at Fordham University will help address these workforce needs by providing scholarships to educate a new breed of cybersecurity professionals trained in data science methods and tools. Fordham SFS recipients will earn an M.S. in Cybersecurity with either a concentration in Data Science or an Advanced Certificate in Data Science for Cybersecurity. The program will afford students a well-rounded cybersecurity education, including its technical and ethical components, which are vital for government positions. The project team will leverage recent awards made to Fordham focused on increasing diversity, including GenCyber and National Security Agency Cybersecurity Education Diversity Initiative awards. These and other efforts by the project team aim to increase the participation of groups who have thus far remained underrepresented in the cybersecurity workforce.The goal of inspiring new cybersecurity personnel towards a career in government service will benefit from Fordham’s collaboration with numerous government agencies, its small class sizes, and numerous opportunities to participate in research and outreach activities, such as cyber-defense competitions. Students will have the option of pursuing a cyber-operations or a policy/law/management track for the cybersecurity coursework. Data science coursework will provide students with the programming skills, tools, and experience required to manipulate, analyze, and visualize large and complex datasets. The student-centered curriculum that leverages the synergies between the traditional cybersecurity and data science curricula will result in cybersecurity professionals who are well-prepared to meet evolving cybersecurity threats to our nation’s information systems and data infrastructure. This project is supported by the CyberCorps(R) Scholarship for Service (SFS) program, which funds proposals establishing or continuing scholarship programs in cybersecurity and aligns with the U.S. National Cyber Strategy to develop a superior cybersecurity workforce. Following graduation, scholarship recipients are required to work in cybersecurity for a Federal, state, local, or tribal Government organization for the same duration as their scholarship support.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.
随着越来越复杂和多样化的网络攻击变得普遍,至关重要的是,训练有素且敏捷的网络安全专业人员进入行业和政府职位至关重要。这些专业人员应该擅长分析现代计算系统生成的大量数据,以促进按规模和确定新攻击所需的速率处理。福特汉姆大学的网络科目(R)服务奖学金(SFS)项目将通过提供科学来教育接受数据科学方法和工具培训的新型网络安全专业人员,以帮助满足这些劳动力需求。 Fordham SFS接收者将获得硕士学位。在网络安全方面,数据科学集中度或网络安全数据科学的高级证书。该计划将为学生提供全面的网络安全教育,包括其技术和道德组成部分,这对于政府职位至关重要。项目团队将利用最近向福特汉姆颁发的奖项,致力于增加多样性,包括Gencyber和国家安全局网络安全教育多样性倡议奖。项目团队的这些努力旨在增加迄今为止在网络安全劳动力中人数不足的团队的参与。激励新的网络安全人员朝政府服务事业中受益的目标将从福特汉姆与众多政府机构,其小型机构,其小型班级的合作,以及参与研究和暴动活动中的众多机会,例如Cyber​​each Actives,例如Cybeber-Defsenss,将受益于政府服务。学生将可以选择进行网络操作或网络安全课程的政策/法律/管理轨道。数据科学课程将为学生提供操纵,分析和可视化大型复杂数据集所需的编程技能,工具和经验。以学生为中心的课程来利用传统网络安全和数据科学课程之间的协同作用,将导致网络安全专业人员有足够的准备,他们已经准备好应对不断发展的网络安全对我们国家信息系统和数据基础架构的威胁。该项目得到了网络科目(R)服务奖学金(SFS)计划的支持,该计划资助了建立或持续的网络安全科学计划的建议,并与美国国家网络战略保持一致,以开发出色的网络安全劳动力。毕业后,奖学金获得者必须在与科学支持相同的持续时间内为联邦,州,地方或部落政府组织的网络安全工作。该奖项反映了NSF的法定任务,并被认为是通过基金会的知识分子优点和更广泛的影响审查标准的评估来评估。

项目成果

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Thaier Hayajneh其他文献

Event Detection through Differential Pattern Mining in Cyber-Physical Systems[SCI&EI检索]
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    7.2
  • 作者:
    Md Zakirul Alam Bhuiyan;Jie Wu;Gary M. Weiss;Thaier Hayajneh;Tian Wang;Guojun Wang
  • 通讯作者:
    Guojun Wang

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