Low-Interception Waveform: To Prevent the Recognition of Spectrum Waveform Modulation via Adversarial Examples

01/20/2022
by   Haidong Xie, et al.
0

Deep learning is applied to many complex tasks in the field of wireless communication, such as modulation recognition of spectrum waveforms, because of its convenience and efficiency. This leads to the problem of a malicious third party using a deep learning model to easily recognize the modulation format of the transmitted waveform. Some existing works address this problem directly using the concept of adversarial examples in the image domain without fully considering the characteristics of the waveform transmission in the physical world. Therefore, we propose a low-intercept waveform (LIW) generation method that can reduce the probability of the modulation being recognized by a third party without affecting the reliable communication of the friendly party. Our LIW exhibits significant low-interception performance even in the physical hardware experiment, decreasing the accuracy of the state of the art model to approximately 15% with small perturbations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/20/2022

Adversarial Jamming for a More Effective Constellation Attack

The common jamming mode in wireless communication is band barrage jammin...
research
06/10/2019

On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis

An important modulation technique for Internet of Things (IoT) is the on...
research
02/26/2022

Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression

Future communication networks must address the scarce spectrum to accomm...
research
04/02/2023

AMC-Net: An Effective Network for Automatic Modulation Classification

Automatic modulation classification (AMC) is a crucial stage in the spec...
research
09/04/2020

Learning Constellation Map with Deep CNN for Accurate Modulation Recognition

Modulation classification, recognized as the intermediate step between s...
research
07/12/2020

Recognition and evaluation of constellation diagram using deep learning based on underwater wireless optical communication

Abstract. In this paper, we proposed a method of constellation diagram r...
research
03/07/2018

FQAM-FBMC Design and Its Application to Machine Type Communication

In this paper, we propose a novel waveform design which efficiently comb...

Please sign up or login with your details

Forgot password? Click here to reset