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; 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。