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Distributed Computing

, Volume 31, Issue 6, pp 419–439 | Cite as

A resource-competitive jamming defense

  • Valerie King
  • Seth Pettie
  • Jared Saia
  • Maxwell Young
Article
  • 99 Downloads

Abstract

Consider a scenario where Alice wishes to send a message m to Bob in a time-slotted wireless network. However, there exists an adversary, Carol, who aims to prevent the transmission of m by jamming the communication channel. There is a per-slot cost of 1 to send, receive or jam m on the channel, and we are interested in how much Alice and Bob need to spend relative to Carol in order to guarantee communication. Our approach is to design an algorithm in the framework of resource-competitive analysis where the cost incurred by correct network devices (i.e., Alice and Bob) is parameterized by the cost incurred by faulty devices (i.e., Carol). We present an algorithm that guarantees the successful transmission of m and has the following property: if Carol incurs a cost of \(T\) to jam, then both Alice and Bob have a cost of \(O(T^{\varphi - 1} + 1)=O(T^{.62}+1)\) in expectation, where \(\varphi = (1+ \sqrt{5})/2\) is the golden ratio. In other words, it possible for Alice and Bob to communicate while incurring asymptotically less cost than Carol. We generalize to the case where Alice wishes to send m to n receivers, and we achieve a similar result. Our findings hold even if (1) \(T\) is unknown to either party; (2) Carol knows the algorithms of both parties, but not their random bits; (3) Carol can jam using knowledge of past actions of both parties; and (4) Carol can jam reactively, so long as there is sufficient network traffic in addition to m.

Keywords

Resource-competitive algorithms Jamming attacks Wireless sensor networks Internet of things Security 

Notes

Acknowledgements

We thank Martin Karsten, Srinivasan Keshav, and James Horey for their valuable comments.

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Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of VictoriaVictoriaCanada
  2. 2.Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborUSA
  3. 3.Department of Computer ScienceUniversity of New MexicoAlbuquerqueUSA
  4. 4.Computer Science and Engineering DepartmentMississippi State UniversityMississippi StateUSA

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