5G NR Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation

Lichtman, Marc; Rao, Raghunandan M.; Marojevic, Vuk; Reed, Jeffrey H.; Jover, Roger Piqueras

doi:10.1109/iccw.2018.8403769

Cited by 57 publications

(25 citation statements)

References 8 publications

(12 reference statements)

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“…This information is broadcasted on PRACH, which takes the form of a Zadoff-Chu sequence that embeds a value used to identify the UE temporarily. Despite the large number of possible locations, and the high complexity needed to determine the positions in real-time, jamming PRACH is still feasible [4]. Furthermore, if the jammer does not succeed in determining these locations, it can flood the channel with an invalid preamble as the 5G NR does not specify what it should be done in this scenario.…”

Section: Vulnerableness Of Rach To Jammingmentioning

confidence: 99%

Smart Jamming Attacks in 5G New Radio: A Review

Arjoune

Faruque

2020

2020 10th Annual Computing and Communication Workshop and Conference (CCWC)

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The fifth generation of wireless cellular networks (5G) is expected to be the infrastructure for emergency services, natural disasters rescue, public safety, and military communications. 5G, as any previous wireless cellular network, is vulnerable to jamming attacks, which create deliberate interference to hinder the communication of legitimate users. Therefore, jamming 5G networks can be a real threat to public safety. Thus, there is a strong need to investigate to what extent these networks are vulnerable to jamming attacks. For this investigation, we consider the 3GPP standard released in 2017, which is widely accepted as the primary reference for the deployment of these networks. First, we describe the key elements of 5G New Radio (NR) architecture, such as different channels and signals exchanged between the base station and user equipment. Second, we conduct an in-depth review of the jamming attack models and we assess the 5G NR vulnerabilities to these jamming attacks. Then, we present the state-of-the-art detection and mitigation techniques, and we discuss their suitability to defeat smart jammers in 5G wireless networks. Finally, we provide some recommendations and future research directions at the end of this paper.

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Section: Vulnerableness Of Rach To Jammingmentioning

confidence: 99%

Smart Jamming Attacks in 5G New Radio: A Review

Arjoune

Faruque

2020

2020 10th Annual Computing and Communication Workshop and Conference (CCWC)

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“…One 5G property that mitigates jamming is its wide range of frequency use. Specifically, using frequencies greater than 24GHz inhibits jamming, because of the difficulty of building a jammer for cells operating above 24GHz (Lichtman et al 2018). In 5G networks Primary and Secondary Synchronization Signals (PSS and SSS) are control signals which allow a device to identify base stations with low SINR.…”

Section: Jammingmentioning

confidence: 99%

“…In 5G networks Primary and Secondary Synchronization Signals (PSS and SSS) are control signals which allow a device to identify base stations with low SINR. This makes them resilient to jamming because it requires an attacker to use "more jamming power to successfully jam the signal" (Lichtman et al 2018).…”

Section: Jammingmentioning

confidence: 99%

5G device-to-device communication security and multipath routing solutions

et al. 2019

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Through direct communication, device-to-device (D2D) technology can increase the overall throughput, enhance the coverage, and reduce the power consumption of cellular communications. Security will be of paramount importance in 5G, because 5G devices will directly affect our safety, such as by steering self-driving vehicles and controlling health care applications. 5G will be supporting millions of existing devices without adequate built-in security, as well as new devices whose extreme computing power will make them attractive targets for hackers. This paper presents a survey of the literature on security problems relating to D2D communications in mobile 5G networks. Issues include eavesdropping, jamming, primary user emulation attack, and injecting attack. Because multipath routing emerges as a strategy that can help combat many security problems, particularly eavesdropping, the paper contains an extensive discussion of the security implications of multipath routing. Finally, the paper describes results of a simulation that tests three path selection techniques inspired by the literature. The simulation reveals that routing information through interference disjoint paths most effectively inhibits eavesdropping.

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“…The second group is the so-called intentional interference (i.e., jamming) mainly used in the military or security to disrupt enemy communication systems or counteract radio systems in a protected area (i.e., electromagnetic curtain [ 11 ]), e.g., in airports, buildings, and infrastructure of strategic importance. Examples of jamming 5G systems are presented in [ 12 , 13 ]. The remainder of the paper focuses on non-intentional interferences.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Downlink Interference in Massive MIMO 5G Macro-Cell

Bechta¹,

Ziółkowski

Kelner

et al. 2021

Sensors

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Multi-beam antenna systems are the basic technology used in developing fifth-generation (5G) mobile communication systems. In practical implementations of 5G networks, different approaches are used to enable a massive multiple-input-multiple-output (mMIMO) technique, including a grid of beams, zero-forcing, or eigen-based beamforming. All of these methods aim to ensure sufficient angular separation between multiple beams that serve different users. Therefore, ensuring the accurate performance evaluation of a realistic 5G network is essential. It is particularly crucial from the perspective of mMIMO implementation feasibility in given radio channel conditions at the stage of network planning and optimization before commercial deployment begins. This paper presents a novel approach to assessing the impact of a multi-beam antenna system on an intra-cell interference level in a downlink, which is important for the accurate modeling and efficient usage of mMIMO in 5G cells. The presented analysis is based on geometric channel models that allow the trajectories of propagation paths to be mapped and, as a result, the angular power distribution of received signals. A multi-elliptical propagation model (MPM) is used and compared with simulation results obtained for a statistical channel model developed by the 3rd Generation Partnership Project (3GPP). Transmission characteristics of propagation environments such as power delay profile and antenna beam patterns define the geometric structure of the MPM. These characteristics were adopted based on the 3GPP standard. The obtained results show the possibility of using the presented novel MPM-based approach to model the required minimum separation angle between co-channel beams under line-of-sight (LOS) and non-LOS conditions, which allows mMIMO performance in 5G cells to be assessed. This statement is justified because for 80% of simulated samples of intra-cell signal-to-interference ratio (SIR), the difference between results obtained by the MPM and commonly used 3GPP channel model was within 2 dB or less for LOS conditions. Additionally, the MPM only needs a single instance of simulation, whereas the 3GPP channel model requires a time-consuming and computational power-consuming Monte Carlo simulation method. Simulation results of intra-cell SIR obtained this way by the MPM approach can be the basis for spectral efficiency maximization in mMIMO cells in 5G systems.

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5G NR Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation

Cited by 57 publications

References 8 publications

Smart Jamming Attacks in 5G New Radio: A Review

Smart Jamming Attacks in 5G New Radio: A Review

5G device-to-device communication security and multipath routing solutions

Modeling of Downlink Interference in Massive MIMO 5G Macro-Cell

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