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Collaborative Research: NeTS: JUNO3: Leveraging Heterogeneous Programmable Data Planes for Security and Privacy of Cellular Networks, 5G & Beyond

Collaborative Research: NeTS: JUNO3: Leveraging Heterogeneous Programmable Data Planes for Security and Privacy of Cellular Networks, 5G & Beyond
合作研究:NetS:JUNO3:利用异构可编程数据平面实现蜂窝网络、5G 的安全和隐私
批准号:
2210379
负责人:
Kadangode Ramakrishnan
金额:
$22.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31

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中文摘要
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英文摘要
Securing “5G and beyond” cellular networks is critical to support the growing traffic from mobile and IoT devices. Significant parts of the cellular network infrastructure are being implemented on software-based environments. The shift to a disaggregated, virtualized cellular core network may result in an increased attack surface and greater vulnerability. Slow attacks, which attempt to avoid notice, can be damaging as they cannot be easily detected, and generally require the memory and computational capacity of end-host security middleboxes to detect or prevent them. Likewise, attackers seeking to violate user-privacy by eavesdropping on communication, cannot be easily prevented, especially at large scale. These threats leave both cellular users and operators vulnerable to attacks. This joint US-Japan project seeks to provide strong security monitoring and privacy protection solutions that exploit the high speed of programmable switches, the increased capabilities of programmable network interface cards, and the memory/computational capacity of end-host servers. By leveraging the strengths of each of these data plane components, the project will develop an efficient and performant cellular network security solution. To achieve this goal, this joint US-Japan project will pursue technical tasks that will be collaboratively pursued by the PIs based in the US and Japan. First, the team will design a heterogeneous data plane framework that cohesively combines multiple data plane devices for network function processing. The approach will use a collaborative filtering system, where most of the traffic is processed only by high-speed programmable switches that can easily extract aggregated, coarse-grained metrics. Suspicious traffic will be redirected to programmable network interface cards, or the host as necessary, for further inspection and metrics collection. Second, the project will develop real-time monitoring of cellular traffic, leveraging the cellular core network as a key vantage point. Monitoring at the cellular core can not only effectively detect and thwart data plane-based attacks, but also those on the control plane. It is in the unique position of being able to correlate between data and control plane state to further improve upon existing approaches to detect security attacks. Finally, the project will design privacy protection mechanisms that ensure anonymity of users in the face of fingerprinting attacks. The approach will leverage traffic morphing techniques that leverage the entire range of capabilities of a multi-tier, programmable, heterogeneous data plane framework, to enable high-speed operation. The proposed techniques will have significant societal impact by providing strong threat prevention and privacy preservation for cellular network users and their traffic.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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