Low-cost Influence-Limiting Defense against Adversarial Machine Learning Attacks in Cooperative Spectrum Sensing

Zhengping Luo, Shangqing Zhao, Rui Duan, Zhuo Lu, Yalin E. Sagduyu, Jie Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cooperative spectrum sensing aims to improve the reliability of spectrum sensing by individual sensors for better utilization of the scarce spectrum bands, which gives the feasibility for secondary spectrum users to transmit their signals when primary users remain idle. However, there are various vulnerabilities experienced in cooperative spectrum sensing, especially when machine learning techniques are applied. The influence-limiting defense is proposed as a method to defend the data fusion center when a small number of spectrum sensing devices is controlled by an intelligent attacker to send erroneous sensing results. Nonetheless, this defense suffers from a computational complexity problem. In this paper, we propose a low-cost version of the influence-limiting defense and demonstrate that it can decrease the computation cost significantly (the time cost is reduced to less than 20% of the original defense) while still maintaining the same level of defense performance.

Original languageEnglish (US)
Title of host publicationWiseML 2021 - Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning
PublisherAssociation for Computing Machinery, Inc
Pages55-60
Number of pages6
ISBN (Electronic)9781450385619
DOIs
StatePublished - Jun 28 2021
Event3rd ACM Workshop on Wireless Security and Machine Learning, WiseML 2021 - Virtual, Online, United Arab Emirates
Duration: Jul 2 2021 → …

Publication series

NameWiseML 2021 - Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning

Conference

Conference3rd ACM Workshop on Wireless Security and Machine Learning, WiseML 2021
Country/TerritoryUnited Arab Emirates
CityVirtual, Online
Period7/2/21 → …

Keywords

  • adversarial machine learning
  • attack
  • Cooperative spectrum sensing
  • data fusion
  • defense
  • machine learning

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications

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