Adversarial Threats to Automatic Modulation Open Set Recognition in Wireless Networks

Fuente: arXiv
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Main Authors: Yang, Yandie, Zhang, Sicheng, Li, Kuixian, Tian, Qiao, Lin, Yun
Format: Preprint
Published: 2024
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author Yang, Yandie
Zhang, Sicheng
Li, Kuixian
Tian, Qiao
Lin, Yun
author_facet Yang, Yandie
Zhang, Sicheng
Li, Kuixian
Tian, Qiao
Lin, Yun
contents Automatic Modulation Open Set Recognition (AMOSR) is a crucial technological approach for cognitive radio communications, wireless spectrum management, and interference monitoring within wireless networks. Numerous studies have shown that AMR is highly susceptible to minimal perturbations carefully designed by malicious attackers, leading to misclassification of signals. However, the adversarial security issue of AMOSR has not yet been explored. This paper adopts the perspective of attackers and proposes an Open Set Adversarial Attack (OSAttack), aiming at investigating the adversarial vulnerabilities of various AMOSR methods. Initially, an adversarial threat model for AMOSR scenarios is established. Subsequently, by analyzing the decision criteria of both discriminative and generative open set recognition, OSFGSM and OSPGD are proposed to reduce the performance of AMOSR. Finally, the influence of OSAttack on AMOSR is evaluated utilizing a range of qualitative and quantitative indicators. The results indicate that despite the increased resistance of AMOSR models to conventional interference signals, they remain vulnerable to attacks by adversarial examples.
format Preprint
id arxiv_https___arxiv_org_abs_2405_05022
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Adversarial Threats to Automatic Modulation Open Set Recognition in Wireless Networks
Yang, Yandie
Zhang, Sicheng
Li, Kuixian
Tian, Qiao
Lin, Yun
Cryptography and Security
Social and Information Networks
Automatic Modulation Open Set Recognition (AMOSR) is a crucial technological approach for cognitive radio communications, wireless spectrum management, and interference monitoring within wireless networks. Numerous studies have shown that AMR is highly susceptible to minimal perturbations carefully designed by malicious attackers, leading to misclassification of signals. However, the adversarial security issue of AMOSR has not yet been explored. This paper adopts the perspective of attackers and proposes an Open Set Adversarial Attack (OSAttack), aiming at investigating the adversarial vulnerabilities of various AMOSR methods. Initially, an adversarial threat model for AMOSR scenarios is established. Subsequently, by analyzing the decision criteria of both discriminative and generative open set recognition, OSFGSM and OSPGD are proposed to reduce the performance of AMOSR. Finally, the influence of OSAttack on AMOSR is evaluated utilizing a range of qualitative and quantitative indicators. The results indicate that despite the increased resistance of AMOSR models to conventional interference signals, they remain vulnerable to attacks by adversarial examples.
title Adversarial Threats to Automatic Modulation Open Set Recognition in Wireless Networks
topic Cryptography and Security
Social and Information Networks
url https://arxiv.org/abs/2405.05022