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.
夺旗 (CTF) 活动是培训下一代网络安全人才的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网络攻击和/或防御实践经验,而这些经验是很难获得的。以往的CTF活动涵盖了许多主题,例如汽车和投票机,并且非常成功地吸引了参与者并激励他们从事网络安全职业。随着5G网络在全球范围内逐步铺开,其安全性已变得越来越重要。一个很大的关注,使得它也该项目的新颖之处在于将 5G 网络整合到 CTF 竞赛中,旨在加强和转变现有的网络安全教育和劳动力发展活动。该项目的更广泛意义和重要性在于,它将提供一个新的场地。培训未来网络安全人员的网络攻击和/或防御实践技能,并帮助他们获得 5G 网络的初步经验。该项目旨在开发一个名为 CTF5G 的开放云平台,该平台可以自动创建专注于 5G 网络的 CTF 游戏实例。 5G网络安全解决了构建CTF5G所涉及的技术挑战,包括如何实现CTF竞赛的快速设置(敏捷性)、如何控制针对不同类型CTF竞赛的5G网络中植入的漏洞(可控性)、如何制作CTF竞赛。 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:第一阶段利用容器化 5G 网络。第二阶段将不同类型的漏洞植入普通 5G 网络模块中,以组成可利用的 5G 网络。当CTF5G部署在公有云上时,CTF5G将采用系统扩展和模块共享等技术来扩大服务的用户数量。作为基于开放云的CTF平台,CTF5G将增强个体的多样性。获得网络安全和 5G 技术教育机会的人,包括来自代表性不足群体的人。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
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Guanhua Yan其他文献
Finding common ground among experts' opinions on data clustering: With applications in malware analysis
在专家关于数据聚类的观点中寻找共同点:在恶意软件分析中的应用
- DOI:
10.1109/icde.2014.6816636 - 发表时间:
2014-05-19 - 期刊:
- 影响因子:0
- 作者:
Guanhua Yan - 通讯作者:
Guanhua Yan
Temperature‐dependent study reveals that dynamics of hydrophobic residues plays an important functional role in the mitochondrial Tim9–Tim10 complex
温度依赖性研究表明疏水残基的动力学在线粒体 Tim9–Tim10 复合物中起着重要的功能作用
- DOI:
10.1002/prot.23224 - 发表时间:
2012-02-01 - 期刊:
- 影响因子:0
- 作者:
E. Ivanova;Jiayun Pang;T. Jowitt;Guanhua Yan;J. Warwicker;M. Sutcliffe;Hui Lu - 通讯作者:
Hui Lu
Emulation-Instrumented Fuzz Testing of 4G/LTE Android Mobile Devices Guided by Reinforcement Learning
强化学习引导下的 4G/LTE Android 移动设备仿真仪器模糊测试
- DOI:
10.1007/978-3-319-98989-1_2 - 发表时间:
2018-09-03 - 期刊:
- 影响因子:3.6
- 作者:
Kaiming Fang;Guanhua Yan - 通讯作者:
Guanhua Yan
Improving Efficiency of Link Clustering on Multi-core Machines
提高多核机器上链路集群的效率
- DOI:
10.1109/icdcs.2017.126 - 发表时间:
2017-06-01 - 期刊:
- 影响因子:0
- 作者:
Guanhua Yan - 通讯作者:
Guanhua Yan
IoTInfer: Automated Blackbox Fuzz Testing of IoT Network Protocols Guided by Finite State Machine Inference
IoTInfer:有限状态机推理引导的物联网网络协议自动黑盒模糊测试
- DOI:
10.1109/jiot.2022.3182589 - 发表时间:
2022-11-15 - 期刊:
- 影响因子:10.6
- 作者:
Zhan Shu;Guanhua Yan - 通讯作者:
Guanhua Yan
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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