Multi-Agent Reinforcement Learning Approaches to RF Fingerprint Enhancement-Reference-Cited by-同舟云学术

Multi-Agent Reinforcement Learning Approaches to RF Fingerprint Enhancement

Published:2021-06-28 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning
language:
Short-container-title:

Author:

Carmack Joseph¹,Schmidt Steve¹,Kuzdeba Scott¹

Affiliation:

1. BAE Systems, Inc

Funder

Defense Advanced Research Projects Agency

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3468218.3469037

Reference30 articles.

1. 2019. Radio Frequency Machine Learning Systems (RFMLS). https://www.darpa.mil/program/radio-frequency-machine-learning-systems. 2019. Radio Frequency Machine Learning Systems (RFMLS). https://www.darpa.mil/program/radio-frequency-machine-learning-systems.

2. 2020. Analog Devices RF Transceivers Support from MATLAB and Simulink - Hardware Support - MATLAB & Simulink. https://www.mathworks.com/hardware-support/analog-devices-rf-transceivers.html. 2020. Analog Devices RF Transceivers Support from MATLAB and Simulink - Hardware Support - MATLAB & Simulink. https://www.mathworks.com/hardware-support/analog-devices-rf-transceivers.html.

3. 2020. RF and SDR System Support with Analog Devices - MATLAB & Simulink. https://www.mathworks.com/campaigns/products/partner/rf-sdr-system-support-with-analog-devices.html. 2020. RF and SDR System Support with Analog Devices - MATLAB & Simulink. https://www.mathworks.com/campaigns/products/partner/rf-sdr-system-support-with-analog-devices.html.

4. G. Brockman V. Cheung L. Pettersson J. Schneider J. Schulman J. Tang and W. Zaremba. 2016. OpenAI Gym. (2016). arXiv:1606.01540 G. Brockman V. Cheung L. Pettersson J. Schneider J. Schulman J. Tang and W. Zaremba. 2016. OpenAI Gym. (2016). arXiv:1606.01540

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Removing the RF Fingerprint: A Least Squares Approach to Compensate for a Device's Hardware Impairments;MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM);2022-11-28

2. Systems View to Designing RF Fingerprinting for Real-World Operations;Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning;2022-05-16

3. RF Fingerprinting with Dilated Causal Convolutions–An Inherently Explainable Architecture;2021 55th Asilomar Conference on Signals, Systems, and Computers;2021-10-31