Education DCL: EAGER: Building a Capture-The-Flag Platform for 5G Network Security
教育 DCL:EAGER:构建 5G 网络安全的夺旗平台
基本信息
- 批准号:2335369
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-10-01 至 2025-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Capture The Flag (CTF) events are one of the most popular venues to train next-generation cybersecurity workforce. By participating in CTF competitions, participants can gain valuable hands-on cyber-attack and/or defense experiences, which are hard to obtain from in-class courses. Previous CTF events have covered many themes, such as automobiles and voting machines, and were quite successful in engaging participants and motivating them to pursue career in cyber security. While 5G networks are gradually rolled out globally, their security has become a great concern, making it also an excellent topic for new CTF contests. The project’s novelties are integration of 5G networks into CTF competitions with the goal to enhance and transform the existing cybersecurity education and workforce development activities. The project's broader significance and importance are that it will offer a new venue to train future cybersecurity workforce with cyber offense and/or defense hands-on skills and help them gain a first experience with 5G networks. The project aims to develop an open cloud-based platform called CTF5G, which can automatically create CTF game instances focusing on 5G network security. It tackles the technical challenges involved in building CTF5G, including how to enable a quick setup of CTF contests (agility), how to control the vulnerabilities implanted within 5G networks for different types of CTF contests (controllability), how to make CTF contests fair to all participants (accountability), and how to scale up the number of users on a public cloud (scalability). The project includes four stages. The first stage leverages containerized 5G network modules to automate workflow for CTF contests. The second stage implants different types of vulnerabilities into vanilla 5G network modules to compose exploitable 5G networks. The third stage explores techniques to track players' activities within the platform and catch foul plays early in CTF contests. The final stage applies techniques such as system debloating and module sharing to scale up the number of users served when CTF5G is deployed on a public cloud. As an open cloud based CTF platform, CTF5G will enhance the diversity of individuals who have access to educational opportunities in cybersecurity and 5G technologies, including those from underrepresented groups.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.
Capture The Flag(CTF)活动是培训下一代网络安全员工最受欢迎的场所之一。通过参加CTF比赛,参与者可以获得宝贵的动手网络攻击和/或防御经验,这是很难从课堂课程中获得。以往的CTF活动涵盖了许多主题,例如汽车和投票机,并且在吸引参与者并激励他们从事网络安全职业方面非常成功。随着5G网络在全球范围内逐步推出,其安全性已成为一个非常令人担忧的问题,这也使其成为新的CTF竞赛的一个很好的话题。该项目的创新之处在于将5G网络整合到CTF竞赛中,旨在加强和改变现有的网络安全教育和劳动力发展活动。该项目更广泛的意义和重要性在于,它将提供一个新的场所,以培训未来的网络安全人员,掌握网络攻击和/或防御的实际技能,并帮助他们获得5G网络的第一次体验。该项目旨在开发一个名为CTF 5G的开放式云平台,该平台可以自动创建专注于5G网络安全的CTF游戏实例。它解决了构建CTF 5G所涉及的技术挑战,包括如何快速设置CTF竞赛(敏捷性),如何控制5G网络中植入的不同类型CTF竞赛的漏洞(可控性),如何使CTF竞赛对所有参与者公平(问责制),以及如何扩大公共云上的用户数量(可扩展性)。该项目包括四个阶段。第一阶段利用集装箱化的5G网络模块来自动化CTF竞赛的工作流程。第二阶段将不同类型的漏洞植入到普通5G网络模块中,以构成可利用的5G网络。第三阶段探索技术,以跟踪球员的活动在平台上,并赶上犯规早在CTF比赛。最后一个阶段应用了系统迁移和模块共享等技术,以扩大CTF 5G在公共云上部署时所服务的用户数量。作为一个开放的基于云的CTF平台,CTF 5G将提高获得网络安全和5G技术教育机会的个人的多样性,包括那些来自代表性不足的群体。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响力审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
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专利数量(0)
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Guanhua Yan其他文献
Sim-Watchdog: Leveraging Temporal Similarity for Anomaly Detection in Dynamic Graphs
Sim-Watchdog:利用时间相似性进行动态图中的异常检测
- DOI:
10.1109/icdcs.2014.24 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Guanhua Yan;S. Eidenbenz - 通讯作者:
S. Eidenbenz
Improving Efficiency of Link Clustering on Multi-core Machines
- DOI:
10.1109/icdcs.2017.126 - 发表时间:
2017-06 - 期刊:
- 影响因子:0
- 作者:
Guanhua Yan - 通讯作者:
Guanhua Yan
Peri-Watchdog: Hunting for hidden botnets in the periphery of online social networks
- DOI:
10.1016/j.comnet.2012.07.016 - 发表时间:
2013-02 - 期刊:
- 影响因子:0
- 作者:
Guanhua Yan - 通讯作者:
Guanhua Yan
Containing Viral Spread on Sparse Random Graphs: Bounds, Algorithms, and Experiments
在稀疏随机图上遏制病毒传播:界限、算法和实验
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
M. Bradonjic;Michael Molloy;Guanhua Yan - 通讯作者:
Guanhua Yan
Measuring the effectiveness of infrastructure-level detection of large-scale botnets
衡量大规模僵尸网络基础设施级检测的有效性
- DOI:
10.1109/iwqos.2011.5931312 - 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Y. Zeng;Guanhua Yan;S. Eidenbenz;K. Shin - 通讯作者:
K. Shin
Guanhua Yan的其他文献
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{{ truncateString('Guanhua Yan', 18)}}的其他基金
CAREER: Proactive Techniques for Enhancing Security and Resilience of Mobile Communication Infrastructure
职业:增强移动通信基础设施安全性和弹性的主动技术
- 批准号:
1943079 - 财政年份:2020
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
TWC: Small: A Moving Target Approach to Enhancing Machine Learning-Based Malware Defense
TWC:小型:增强基于机器学习的恶意软件防御的移动目标方法
- 批准号:
1618631 - 财政年份:2016
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
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