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Massive reactive smartphone-based jamming using arbitrary waveforms and adaptive power control

Published:18 July 2017Publication History

ABSTRACT

It is not commonly known that off-the-shelf smartphones can be converted into versatile jammers. To understand how those jammers work and how well they perform, we implemented a jamming firmware for the Nexus 5 smartphone. The firmware runs on the real-time processor of the Wi-Fi chip and allows to reactively jam Wi-Fi networks in the 2.4 and 5 GHz bands using arbitrary waveforms stored in IQ sample buffers. This allows us to generate a pilot-tone jammer on off-the-shelf hardware. Besides a simple reactive jammer, we implemented a new acknowledging jammer that selectively jams only targeted data streams of a node while keeping other data streams of the same node flowing. To lower the increased power consumption of this jammer, we implemented an adaptive power control algorithm. We evaluated our implementations in friendly jamming scenarios to oppress non-compliant Wi-Fi transmissions and to protect otherwise vulnerable devices in industrial setups. Our results show that we can selectively hinder Wi-Fi transmissions in the vicinity of our jamming smartphone leading to an increased throughput for other nodes or no blockage of non-targeted streams on a jammed node. Consuming less than 300 mW when operating the reactive jammer allows mobile operation for more than 29 hours. Our implementation demonstrates that jamming communications was never that simple and available for every smartphone owner, while still allowing surgical jamming precision and energy efficiency. Nevertheless, it involves the danger of abuse by malicious attackers that may take over hundreds of devices to massively jam Wi-Fi networks in wide areas.

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  1. Massive reactive smartphone-based jamming using arbitrary waveforms and adaptive power control

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    • Published in

      cover image ACM Conferences
      WiSec '17: Proceedings of the 10th ACM Conference on Security and Privacy in Wireless and Mobile Networks
      July 2017
      297 pages
      ISBN:9781450350846
      DOI:10.1145/3098243

      Copyright © 2017 ACM

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      Publication History

      • Published: 18 July 2017

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