CRII: NeTS: A Proactive Perspective on Preventing Network Inference: Shifting from Optimized to Dynamic Wireless Network Design

CRII:NeTS:防止网络推理的主动视角:从优化到动态无线网络设计的转变

基本信息

  • 批准号:
    1701394
  • 负责人:
  • 金额:
    $ 6.55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-10-05 至 2018-06-30
  • 项目状态:
    已结题

项目摘要

This project will design strategies to thwart malicious efforts targeting the inference of information from wireless networks. New proactive anti-inference strategies will be developed and tested to make networks more dynamic and less inference-susceptible. The project involves the training of undergraduate and graduate students in network inference/anti-inference theoretical and experimental activities, and is expected to significantly impact the security design of mission-critical wireless networks.Network inference is an effective way to infer the information of network statistics and properties from network measurements. Network inference has enabled a wide range of applications, such as network surveillance, management and diagnosis; however, in certain circumstances, such as wireless networks for military applications, it is important to mask this information to prevent the use of inference for malicious intent. To date, strategies for anti-inference in wireless networks have been overlooked and under-explored. The central goal of this effort is to address the current gap in understanding by exploring the fundamental aspects of proactive strategies that will enable a wide range of anti-inference applications. Specific objectives are to (1) develop a theoretical framework to analyze the behaviors of proactive strategies that enhance network dynamics to achieve anti-inference; (2) reveal the fundamental relationship between the impacts and costs of network dynamics based anti-inference strategies; and (3) implement efficient anti-inference design for network applications. To accomplish these objectives, both deception traffic and routing changing strategies will be utilized to induce higher dynamics in the network to make inference inaccurate. In addition, the cost-benefit impact of these strategies will be examined by shifting from optimized to dynamic network design.
该项目将设计策略,以挫败针对无线网络信息推断信息的恶意努力。将制定和测试新的主动反推理策略,以使网络更具动态性和更少的推理敏感性。该项目涉及在网络推论/反推断理论和实验活动中对本科和研究生的培训,并有望显着影响关键任务 - 无线网络的安全设计。网络推断是从网络测量中推断网络统计信息和属性信息的有效方法。网络推断已实现了广泛的应用程序,例如网络监视,管理和诊断;但是,在某些情况下,例如用于军事应用的无线网络,掩盖此信息以防止推理恶意意图很重要。迄今为止,无线网络中反推理的策略已被忽略和探索。这项努力的核心目标是通过探索主动策略的基本方面来解决当前理解的差距,这些方面将实现广泛的反推理应用。具体目标是(1)开发一个理论框架来分析积极主动策略的行为,从而增强网络动态以实现反推理; (2)揭示了基于网络动态的反推断策略的影响和成本之间的基本关系; (3)为网络应用程序实施有效的反推理设计。为了实现这些目标,欺骗流量和路由变化策略都将用于诱导网络中的更高动态,以使推理不准确。此外,这些策略的成本效益影响将通过从优化的动态网络设计转移来检查。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

暂无数据

数据更新时间:2024-06-01

Zhuo Lu其他文献

Arbuscular mycorrhizal fungi: potential biocontrol agents against the damaging root hemiparasite Pedicularis kansuensis?
丛枝菌根真菌:对抗破坏性根部半寄生虫甘肃马先蒿的潜在生物防治剂?
  • DOI:
    10.1007/s00572-013-0528-5
    10.1007/s00572-013-0528-5
  • 发表时间:
    2013-09
    2013-09
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Sui Xiao-Lin;Li Ai-Rong;Chen Yan;Guan Kai-Yun;Zhuo Lu;Liu Yan-Yan
    Sui Xiao-Lin;Li Ai-Rong;Chen Yan;Guan Kai-Yun;Zhuo Lu;Liu Yan-Yan
  • 通讯作者:
    Liu Yan-Yan
    Liu Yan-Yan
Research on Recommendation System Based on Neural Network and Data Mining
基于神经网络和数据挖掘的推荐系统研究
A Proactive and Deceptive Perspective for Role Detection and Concealment in Wireless Networks
无线网络中角色检测和隐藏的主动和欺骗视角
  • DOI:
  • 发表时间:
    2016
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhuo Lu;Cliff X. Wang;Mingkui Wei
    Zhuo Lu;Cliff X. Wang;Mingkui Wei
  • 通讯作者:
    Mingkui Wei
    Mingkui Wei
Most Cited Computer Networks Articles
被引用最多的计算机网络文章
  • DOI:
  • 发表时间:
    2017
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Luigi Atzori;Antonio Iera;Giacomo Morabito;Michele Nitti;Wenye Wang;Zhuo Lu;M. Berman;Jeffrey S. Chase;Lawrence Landweber;Akihiro Nakao;Max Ott;Dipankar Raychaudhuri;Robert Ricci;I. Seskar;S. Sicari;A. Rizzardi;L. Grieco;A. Coen
    Luigi Atzori;Antonio Iera;Giacomo Morabito;Michele Nitti;Wenye Wang;Zhuo Lu;M. Berman;Jeffrey S. Chase;Lawrence Landweber;Akihiro Nakao;Max Ott;Dipankar Raychaudhuri;Robert Ricci;I. Seskar;S. Sicari;A. Rizzardi;L. Grieco;A. Coen
  • 通讯作者:
    A. Coen
    A. Coen
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前往

Zhuo Lu的其他基金

Collaborative Research: CCSS: Hierarchical Federated Learning over Highly-Dense and Overlapping NextG Wireless Deployments: Orchestrating Resources for Performance
协作研究:CCSS:高密度和重叠的 NextG 无线部署的分层联合学习:编排资源以提高性能
  • 批准号:
    2319781
    2319781
  • 财政年份:
    2023
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: Implementation: Medium: Secure, Resilient Cyber-Physical Energy System Workforce Pathways via Data-Centric, Hardware-in-the-Loop Training
协作研究:实施:中:通过以数据为中心的硬件在环培训实现安全、有弹性的网络物理能源系统劳动力路径
  • 批准号:
    2320973
    2320973
  • 财政年份:
    2023
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: SaTC: CORE: Small: Understanding the Limitations of Wireless Network Security Designs Leveraging Wireless Properties: New Threats and Defenses in Practice
协作研究:SaTC:核心:小型:了解利用无线特性的无线网络安全设计的局限性:实践中的新威胁和防御
  • 批准号:
    2316719
    2316719
  • 财政年份:
    2023
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: SaTC: EDU: A Comprehensive Training Program of AI for 5G and NextG Wireless Network Security
合作研究:SaTC:EDU:5G 和 NextG 无线网络安全人工智能综合培训项目
  • 批准号:
    2321270
    2321270
  • 财政年份:
    2023
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
CAREER: Data-Driven Wireless Networking Designs for Efficiency and Security
职业:数据驱动的无线网络设计以提高效率和安全性
  • 批准号:
    2044516
    2044516
  • 财政年份:
    2021
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Continuing Grant
    Continuing Grant
Collaborative Research: CyberTraining: Pilot: Interdisciplinary Training of Data-Centric Security and Resilience of Cyber-Physical Energy Infrastructures
合作研究:网络培训:试点:以数据为中心的网络物理能源基础设施安全性和弹性的跨学科培训
  • 批准号:
    2017194
    2017194
  • 财政年份:
    2020
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
Collaborative Research: SWIFT: SMALL: Understanding and Combating Adversarial Spectrum Learning towards Spectrum-Efficient Wireless Networking
合作研究:SWIFT:SMALL:理解和对抗对抗性频谱学习以实现频谱高效的无线网络
  • 批准号:
    2029875
    2029875
  • 财政年份:
    2020
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
SaTC: CORE: Small: Towards Secure and Reliable Network Tomography in Wireline and Wireless Networks
SaTC:核心:小型:在有线和无线网络中实现安全可靠的网络层析成像
  • 批准号:
    1717969
    1717969
  • 财政年份:
    2017
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Standard Grant
    Standard Grant
CRII: NeTS: A Proactive Perspective on Preventing Network Inference: Shifting from Optimized to Dynamic Wireless Network Design
CRII:NeTS:防止网络推理的主动视角:从优化到动态无线网络设计的转变
  • 批准号:
    1464114
    1464114
  • 财政年份:
    2015
  • 资助金额:
    $ 6.55万
    $ 6.55万
  • 项目类别:
    Continuing Grant
    Continuing Grant

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