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: 1744261
• 负责人: Linke Guo
• 金额: $ 15万
• 依托单位: SUNY at Binghamton
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744261&HistoricalAwards=false
• 关键词: EAGER; Malicious; Behavior; Detection; Hybrid

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.

为了解决日益严重的频谱稀缺问题，动态频谱接入被设想为一组有前途的新频谱管理范例。虽然它已经使得机会主义接入未充分利用的许可频带，但各种实际因素，例如环境动态，故意干扰和未经授权的传输，阻碍了它的广泛部署。最近发布的FCC规则表明，参与式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效率，这形成了一种新的范式，混合动态频谱共享。然而，次用户与频谱数据库之间频繁交换的信息很容易被恶意用户截获和操纵，这不仅降低了频谱利用率，而且给混合动态频谱接入系统带来了严重的安全隐患。该项目将探索保护未来认知无线电系统的新范式，重点是违规行为检测。该项目的成功将成为在不久的将来提供可靠的无线通信的关键推动因素。该项目将研究新定义的混合动态频谱接入中的几个基本安全挑战。这第一个研究任务将确定新的攻击模式，损害频谱效率，然后提供适应未来无线系统的对策。由于数据库驱动的频谱接入的固有性质，主用户仿真（PUE）攻击者可以检索频谱可用性信息，以在现任用户（IU）不存在时作为现任用户（IU）执行，或者尝试增加次用户的传输功率以干扰当前IU。利用存储在数据库中的检测结果，设计新的检测方案来减轻攻击带来的影响。第二个研究任务是利用物理层方法来检测不同信道模型下的未授权访问。为解决此问题，将使用通道可用性信息来检测恶意次要用户。与此同时，将在兼顾实用性和效率的情况下开发检测机制。此外，该项目包括强大的验证组件，结合了模拟研究，原型设计和实验。因此，它将为跨学科学科提供有效的培训基地，包括无线网络，无线通信和网络安全，所有这些都对未来国家劳动力的多元化专业人员至关重要。

项目成果

Motivating Human-Enabled Mobile Participation for Data Offloading

• DOI: 10.1109/tmc.2017.2773087
• 发表时间: 2018-07
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 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: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
• 作者: Xiaonan Zhang;Pei Huang;Linke Guo;M. Sha

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: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
• 作者: Wenqiang Jin;Mingyan Xiao;Ming Li;Linke Guo

CREAM: Unauthorized Secondary User Detection in Fading Environments

• DOI: 10.1109/mass.2018.00064
• 发表时间: 2018-10
• 期刊: 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)
• 作者: Xiaonan Zhang;Pei Huang;Qi Jia;Linke Guo

Secure and optimized unauthorized secondary user detection in dynamic spectrum access

动态频谱访问中安全且优化的未授权二级用户检测

• DOI: 10.1109/cns.2017.8228639
• 发表时间: 2017
• 期刊: 2017 IEEE Conference on Communications and Network Security (CNS
• 作者: Zhang, Xiaonan;Jia, Qi;Guo, Linke
• 通讯作者: Guo, Linke