EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum Access
EAGER:混合动态频谱访问中的恶意行为检测
基本信息
- 批准号:1744261
- 负责人:
- 金额:$ 15万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-01 至 2019-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
To tackle the ever-increasing spectrum scarcity issue, dynamic spectrum access is envisioned as a set of promising new spectrum management paradigms. Although it has enabled the opportunistic access of underutilized licensed bands, various practical factors, such as environmental dynamics, intentional interference, and unauthorized transmission, hinder it from wide deployment. The recently released FCC rules suggest participatory real-time spectrum sensing can greatly improve the spectrum utilization efficiency for database-driven spectrum sharing, which forms a new paradigm, hybrid dynamic spectrum sharing. However, the frequent information exchanged between secondary users and spectrum database can be easily intercepted and manipulated by malicious users, which not only downgrades the spectrum efficiency but also incurs severe security breaches to the hybrid dynamic spectrum access system. This project will explore new paradigms of safeguarding the future cognitive radio system with focus on non-compliance behavior detection. The success of this project will serve as a key enabler to provide reliable wireless communication in the near future.This project will investigate several fundamental security challenges in the newly defined hybrid dynamic spectrum access. This first research task will identify new attack models that compromise the spectrum efficiency and then provide countermeasures adapted to future wireless systems. Due to the inherent nature of database-driven spectrum access, primary user emulation (PUE) attackers can retrieve the spectrum availability information to either perform as the incumbent user (IU) when it is not present, or try to increase secondary users' transmission power to interfere with present IUs. Featuring the sensing results stored in the database, novel detection schemes will be designed to mitigate the influence brought by the attack. The second research task leverages physical-layer approaches to detect unauthorized access under different channel models. To address this issue, channel availability information will be used to detect malicious secondary users. Meanwhile, the detection mechanisms will be developed with joint consideration on practicality and efficiency. Additionally, the project includes strong validation component that combines simulation study, prototyping, and experimentation. It will thus provide an effective training ground for interdisciplinary subjects including wireless networks, wireless communication, and cybersecurity, all of which are critical to diversified professionals for future national work force.
为了解决不断增加的频谱稀缺问题,将动态频谱访问设想为一组有希望的新频谱管理范式。尽管它使未充分利用的许可频段的机会主义访问能力,但各种实际因素,例如环境动态,故意干扰和未经授权的传播,但仍阻碍了它的广泛部署。最近发布的FCC规则表明,参与性的实时频谱感知可以大大提高数据库驱动的频谱共享的频谱利用率,该频谱共享形成了新的范式,即混合动力频谱共享。但是,在二级用户和光谱数据库之间交换的频繁信息可以很容易被恶意用户拦截和操纵,这不仅降低了频谱效率,而且还会引起严重的安全性漏洞,从而对混合动态频谱访问系统产生了严重的安全漏洞。该项目将探索以违规行为检测为关注的未来认知无线电系统保护未来的认知无线电系统的新范式。该项目的成功将是在不久的将来提供可靠的无线通信的关键推动者。该项目将调查新定义的新定义混合动态频谱访问中的几个基本安全挑战。第一个研究任务将确定损害频谱效率的新攻击模型,然后提供适合未来无线系统的对策。由于数据库驱动的频谱访问的固有性质,主要用户仿真(PUE)攻击者可以在不存在的现有用户(IU)中检索频谱可用性信息,或者在不存在的情况下执行,或者尝试增加二级用户的传输功能以干扰当前的IUS。具有存储在数据库中的传感结果的特征,将设计出新的检测方案,以减轻攻击带来的影响。第二项研究任务利用物理层方法来检测不同渠道模型下未经授权的访问。为了解决此问题,渠道可用性信息将用于检测恶意的二级用户。同时,将与实用性和效率共同考虑检测机制。此外,该项目还包括结合模拟研究,原型和实验的强验证组件。因此,它将为包括无线网络,无线通信和网络安全在内的跨学科主题提供有效的培训场,所有这些都是对多元化专业人员至关重要的未来国家劳动力的关键。
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Motivating Human-Enabled Mobile Participation for Data Offloading
- DOI:10.1109/tmc.2017.2773087
- 发表时间:2018-07
- 期刊:
- 影响因子:7.9
- 作者:Xiaonan Zhang;Linke Guo;Ming Li;Yuguang Fang
- 通讯作者:Xiaonan Zhang;Linke Guo;Ming Li;Yuguang Fang
Incentivizing Relay Participation for Securing IoT Communication
- DOI:10.1109/infocom.2019.8737451
- 发表时间:2019-04
- 期刊:
- 影响因子:0
- 作者:Xiaonan Zhang;Pei Huang;Linke Guo;M. Sha
- 通讯作者:Xiaonan Zhang;Pei Huang;Linke Guo;M. Sha
CREAM: Unauthorized Secondary User Detection in Fading Environments
- DOI:10.1109/mass.2018.00064
- 发表时间:2018-10
- 期刊:
- 影响因子:0
- 作者:Xiaonan Zhang;Pei Huang;Qi Jia;Linke Guo
- 通讯作者:Xiaonan Zhang;Pei Huang;Qi Jia;Linke Guo
If You Do Not Care About It, Sell It: Trading Location Privacy in Mobile Crowd Sensing
- DOI:10.1109/infocom.2019.8737457
- 发表时间:2019-04
- 期刊:
- 影响因子:0
- 作者:Wenqiang Jin;Mingyan Xiao;Ming Li;Linke Guo
- 通讯作者:Wenqiang Jin;Mingyan Xiao;Ming Li;Linke Guo
Practical privacy-preserving spectrum query schemes for database-driven CRNs with multiple service providers
针对具有多个服务提供商的数据库驱动的 CRN 的实用隐私保护频谱查询方案
- DOI:10.1109/cns.2017.8228651
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Xin, Jiajun;Li, Ming;Guo, Linke;Li, Pan
- 通讯作者:Li, Pan
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Linke Guo其他文献
FreeEM: Uncovering Parallel Memory EMR Covert Communication in Volatile Environments
FreeEM:揭示不稳定环境中的并行内存 EMR 隐蔽通信
- DOI:
10.1145/3643832.3661870 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sihan Yu;Jingjing Fu;Chenxu Jiang;ChunChih Lin;Zhenkai Zhang;Long Cheng;Ming Li;Xiaonan Zhang;Linke Guo - 通讯作者:
Linke Guo
User-centric private matching for eHealth networks - A social perspective
以用户为中心的电子医疗网络私人匹配 - 社会视角
- DOI:
10.1109/glocom.2012.6503200 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Linke Guo;Xinxin Liu;Yuguang Fang;Xiaolin Li - 通讯作者:
Xiaolin Li
Linke Guo的其他文献
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{{ truncateString('Linke Guo', 18)}}的其他基金
Collaborative Research: SHF: Medium: Towards Harmonious Federated Intelligence in Heterogeneous Edge Computing via Data Migration
协作研究:SHF:中:通过数据迁移实现异构边缘计算中的和谐联邦智能
- 批准号:
2312616 - 财政年份:2023
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
Collaborative Research: CNS Core: Small: Scalable, Flexible, and Dependable Architecture Design for Heterogeneous Internet of Things
合作研究:CNS核心:小型:异构物联网的可扩展、灵活、可靠的架构设计
- 批准号:
2008049 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CCSS: Collaborative Research: Towards Privacy-Preserving Mobile Crowd Sensing: A Multi-Stage Solution
CCSS:协作研究:迈向保护隐私的移动人群感知:多阶段解决方案
- 批准号:
1949639 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum Access
EAGER:混合动态频谱访问中的恶意行为检测
- 批准号:
1947065 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
SCH: INT: Collaborative Research: Crowd in Action: Human-Centric Privacy-Preserving Data Analytics for Environmental Public Health
SCH:INT:协作研究:人群在行动:以人为本的隐私保护环境公共卫生数据分析
- 批准号:
1949640 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
SCH: INT: Collaborative Research: Crowd in Action: Human-Centric Privacy-Preserving Data Analytics for Environmental Public Health
SCH:INT:协作研究:人群在行动:以人为本的隐私保护环境公共卫生数据分析
- 批准号:
1722731 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CCSS: Collaborative Research: Towards Privacy-Preserving Mobile Crowd Sensing: A Multi-Stage Solution
CCSS:协作研究:迈向保护隐私的移动人群感知:多阶段解决方案
- 批准号:
1710996 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
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- 批准号:72172048
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- 项目类别:面上项目
相似海外基金
EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum Access
EAGER:混合动态频谱访问中的恶意行为检测
- 批准号:
1947065 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
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CCF-BSF:CIF:小:多代理优化算法中恶意行为的识别和隔离
- 批准号:
1714672 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Robust detection of malicious behavior in distributed wireless networks.
分布式无线网络中恶意行为的稳健检测。
- 批准号:
234874366 - 财政年份:2013
- 资助金额:
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Research Grants
Robust Detecting Malicious Accesses to Information Manipulation Based on Behavior Estimation of Software
基于软件行为估计的恶意信息操纵访问鲁棒检测
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