Random-Training-Assisted Pilot Spoofing Detection and Secure Transmission

TL;DR

This paper introduces a random-training-assisted method for detecting pilot spoofing attacks, improving channel estimation, and ensuring secure transmission in wireless systems, with extensive simulations validating its effectiveness.

Contribution

The paper proposes a novel RTA pilot spoofing detection algorithm with a new training mechanism and a ZF-based secure transmission scheme, enhancing detection accuracy and security.

Findings

Effective detection of pilot spoofing attacks.

Improved channel estimation accuracy.

Secure transmission achieved under attack conditions.

Abstract

The pilot spoofing attack is considered as an active eavesdropping activity launched by an adversary during the reverse channel training phase. By transmitting the same pilot signal as the legitimate user, the pilot spoofing attack is able to degrade the quality of legitimate transmission and, more severely, facilitate eavesdropping. In an effort to detect the pilot spoofing attack and minimize its damages, in this paper we propose a novel random-training-assisted (RTA) pilot spoofing detection algorithm. In particular, we develop a new training mechanism by adding a random training phase after the conventional pilot training phase. By examining the difference of the estimated legitimate channels during these two phases, the pilot spoofing attack can be detected accurately. If no spoofing attack is detected, we present a computationally efficient channel estimation enhancement algorithm to further improve the channel estimation accuracy. If the existence of the pilot spoofing attack is identified, a zero-forcing (ZF)-based secure transmission scheme is proposed to protect the confidential information from the active eavesdropper. Extensive simulation results demonstrate that the proposed RTA scheme can achieve efficient pilot spoofing detection, accurate channel estimation, and secure transmission.