Vulnerabilities of Massive MIMO Systems to Pilot Contamination Attacks

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3 Citations (Scopus)

Abstract

We consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination attacks. In our attack model, the attacker aims at minimizing the sum-rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the “achievable individual secrecy rates” under pilot-contamination attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%.

Original languageEnglish (US)
JournalIEEE Transactions on Information Forensics and Security
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

MIMO systems
Base stations
Contamination
Channel state information
Antennas
Throughput

Keywords

  • jamming attack
  • Massive MIMO
  • physical-layer security
  • pilot contamination
  • stochastic optimization

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications

Cite this

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title = "Vulnerabilities of Massive MIMO Systems to Pilot Contamination Attacks",
abstract = "We consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination attacks. In our attack model, the attacker aims at minimizing the sum-rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the “achievable individual secrecy rates” under pilot-contamination attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50{\%}.",
keywords = "jamming attack, Massive MIMO, physical-layer security, pilot contamination, stochastic optimization",
author = "Berk Akgun and Krunz, {Marwan M} and Koyluoglu, {Onur Ozan}",
year = "2018",
month = "1",
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doi = "10.1109/TIFS.2018.2876750",
language = "English (US)",
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AU - Akgun, Berk

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AU - Koyluoglu, Onur Ozan

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N2 - We consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination attacks. In our attack model, the attacker aims at minimizing the sum-rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the “achievable individual secrecy rates” under pilot-contamination attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%.

AB - We consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination attacks. In our attack model, the attacker aims at minimizing the sum-rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the “achievable individual secrecy rates” under pilot-contamination attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%.

KW - jamming attack

KW - Massive MIMO

KW - physical-layer security

KW - pilot contamination

KW - stochastic optimization

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