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Robust Covert Wireless Communications: Fundamental Limits and Algorithms

强大的隐蔽无线通信：基本限制和算法

基本信息

批准号：
2148159
负责人：
Dennis Goeckel
金额：
$ 49.98万
依托单位：
University of Massachusetts Amherst
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
起止时间：
2022-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148159&HistoricalAwards=false
关键词：
Robust Covert Wireless Communications Fundamental

项目摘要

Wireless communication networks form a critical part of the national infrastructure for both civilian and military applications. Because these networks propagate a radio signal that can be readily observed, security and privacy are major concerns. Much of security and privacy research focuses on protecting the content of messages from eavesdroppers, but there are important applications where even the detection of a communication signal's presence by an adversary is undesirable. In a civilian setting, the detection of a signal from an embedded medical device leaks health information, or the detection of encrypted signals transmitted between parties can lead to that communication being shut down by an authoritarian government. In a military setting, the presence of communication signals can be used as a proxy for troop activity. Hence, undetectable or low probability of detection (LPD) communications has motivated significant historical and recent study. Protection against the detection of a radio signal is challenging given recent advances in algorithms and computation. Algorithmic advances through techniques based on artificial intelligence (AI) and computational advances based on quantum computing provide the adversary with a powerful set of tools for developing a signal detector. This has motivated a branch of information systems research initiated by a portion of this research team ten years ago, now termed “covert communications,” that is developing a fundamental understanding of the ability of two parties to communicate without detection by an attentive and capable adversary. This project will develop results in covert communications for the models that underpin radio communications to allow for the protection of messages in the wireless communication systems that are crucial to modern society.For discrete-time additive white Gaussian noise (AWGN) channels, Bash, Goeckel, and Towsley initiated recent covert communications work by demonstrating in 2012 that a transmitter Alice can reliably transmit O(sqrt(n)) bits in n channel uses (and no more) to recipient Bob without detection by an attentive and capable adversary Willie. And nearly all work in covert communications has been performed on discrete-time models, with the implicit understanding that the results would be applicable to the true continuous-time system. But this is not true for important emerging architectures for covert wireless communications; rather, the continuous-time channel must be considered directly. This project will consider the fundamental characterization of covert communication systems as they are considered for implementation in wireless communications through three research thrusts: 1. Foundations of covert communications in continuous-time systems: We focus on performance characterization and design in the face of tools available for the adversary Willie in continuous-time wireless systems: interference cancellation, cyclostationary detectors, and transmitter identification. 2. Covert communications in the presence of environmental interference: Covert communications hidden behind environmental signals is preferable to employing jamming. We focus on covert throughput bounds as a function of the interference dynamics and techniques to achieve those bounds. 3. Learning-based covert communication approaches: We design and analyze deep neural network (DNN)-based covert transceivers by the simultaneous training of an adversary whose performance is used as a regularizer in the training of the transmitter Alice. The training of a diverse workforce in security and privacy is an important aspect of the project. The third thrust that considers AI-based approaches at both the communication parties and the adversary provides an accessible and highly desirable research area for University of Massachusetts undergraduate students in engineering and computer science.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.

无线通信网络是民用和军用国家基础设施的重要组成部分。由于这些网络传播的无线电信号很容易被观察到，因此安全和隐私是主要问题。许多安全和隐私研究都集中在保护消息内容不被窃听，但在一些重要的应用中，甚至不希望对手检测到通信信号的存在。在民用环境中，检测到来自嵌入式医疗设备的信号会泄露健康信息，或者检测到各方之间传输的加密信号会导致专制政府关闭通信。在军事环境中，通信信号的存在可以被用作部队活动的代理。因此，不可检测或低检测概率（LPD）通信激发了重要的历史和最近的研究。考虑到算法和计算的最新进展，防止无线电信号被检测是具有挑战性的。通过基于人工智能（AI）的技术和基于量子计算的计算进步的数学进步为对手提供了一套强大的工具来开发信号检测器。这激发了信息系统研究的一个分支，该分支由该研究团队的一部分在十年前发起，现在被称为“隐蔽通信”，该分支正在对双方在不被细心和有能力的对手发现的情况下进行通信的能力进行基本理解。该项目将为支撑无线电通信的模型开发隐蔽通信的结果，以保护对现代社会至关重要的无线通信系统中的消息。对于离散时间加性白色高斯噪声（AWGN）信道，Bash，Goeckel，和Towsley在2012年通过证明发射器Alice可以可靠地传输O（sqrt（n））来启动最近的秘密通信工作比特在n信道使用（不超过）接收方鲍勃没有检测到一个细心和有能力的对手威利。几乎所有的秘密通信工作都是在离散时间模型上进行的，隐含的理解是，结果将适用于真正的连续时间系统。但是，这是不正确的重要新兴架构的隐蔽无线通信，而是，连续时间信道必须直接考虑。该项目将考虑隐蔽通信系统的基本特征，因为它们被认为是通过三个研究方向在无线通信中实现：1。在连续时间系统中的隐蔽通信的基础：我们专注于性能表征和设计，在面对的工具，可供对手威利在连续时间无线系统：干扰消除，循环平稳检测器和发射机识别。2.环境干扰下的隐蔽通信：隐藏在环境信号后面的隐蔽通信比使用干扰更可取。我们专注于隐蔽的吞吐量界限作为一个功能的干扰动态和技术，以实现这些界限。3.基于学习的隐蔽通信方法：我们通过同时训练对手来设计和分析基于深度神经网络（DNN）的隐蔽收发器，对手的性能被用作发射器Alice训练中的正则化器。在安全和隐私方面培训多样化的劳动力是该项目的一个重要方面。第三个重点是在通信方和对手双方考虑基于AI的方法，为马萨诸塞州大学工程和计算机科学专业的本科生提供了一个可访问的和非常理想的研究领域。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。