Swift Jamming Attack on Frequency Offset Estimation: The Achilles’ Heel of OFDM Systems

Abstract

Frequency offset (FO) refers to the difference in the operating frequencies of two radio oscillators. Failure to compensate for the FO may lead to decoding errors, particularly in OFDM systems. To correct the FO, wireless standards append a publicly known preamble to every frame before transmission. In this paper, we demonstrate how an adversary can exploit the known preamble structure of OFDM-based wireless systems, particularly IEEE802.11a/g/n/ac, to launch a very stealth (low energy/duty cycle) reactive jamming attack against the FO estimation mechanism. In this attack, the adversary quickly detects a transmitted OFDM frame and subsequently jams a tiny part of the preamble that is used for FO estimation at the legitimate receiver. By optimizing the energy and structure of the jamming signal and accounting for frame detection timing errors and unknown channel parameters, we empirically show that the adversary can induce a bit error rate close to 0.5, making the transmission practically irrecoverable. Such vulnerability to FO jamming exists even when the frame is shielded by efficient channel coding. We evaluate the FO estimation attack through simulations and USRP experimentation. We also propose three approaches to mitigate such an attack.

Independence-Checking Coding for OFDM Channel Training Authentication: Protocol Design, Security, Stability, and Tradeoff Analysis

“…The common problem encountered is that the imperishable characteristic of wireless channels, such as the open and shared nature, has always been rendering those technologies vulnerable to the growing denial of service (DoS) attacks [2]. A phenomenon, if we notice, has emerged in the physical (PHY) layer that DoS attacks, with moderate size of the involved network segment and modest implementation complexity, have become increasingly common and potent [3].…”

Two-dimensional anti-jamming communication based on deep reinforcement learning

“…B Y injecting faked or replayed signals, a jammer aims to interrupt the ongoing communication of mobile devices such as smartphones, mobile sensing robots and mobile servers, and even launch denial of service (DoS) attacks in wireless networks [1]- [5]. With the pervasion of smart radio devices such as universal software radio peripherals (USRPs) [6], jammers can cooperatively and flexibly choose their jamming policies to block the mobile devices efficiently [7], [8]. Jammers can even induce the mobile device to enter a specific communication mode and then launch the jamming attacks accordingly.…”

“…Algorithm 2: Hotbooting process 1 Initialize I, K, W , B, E = ∅, and θ (0) * 2 for i = 1, 2, · · · , I do 3 Initialize a emulational environment 4 Initialize SINR (0) and ψ (1) 5 for k = 1, 2, · · · , K do 6 Perform Steps 3 − 21 in Algorithm 1 to choose x (k) , obtain u (k) and observe ϕ (k+1)…”

Hierarchical 2-D Feature Coding for Secure Pilot Authentication in Multi-User Multi-Antenna OFDM Systems: A Reliability Bound Contraction Perspective

“…Orthogonal frequency-division multiplexing (OFDM) technique becomes such a typical victim when it plays an increasing role in modern wireless systems, standards (e.g., LTE, 802.11a/n/ac/ax/ah) or even under tactical scenarios [2]. Without comprehensive precautions against attacks, OFDM technique comes to be sensitive and fragile in the respect of its waveform transmission and receiving which is very vulnerable to various physical-layer attacks [3], [4]. This paper investigates the pilot-aware attack on the channel estimation process in multi-antenna OFDM communications [5].…”