Frequency Hopping against a Powerful Adversary

Emek, Yuval; Wattenhofer, Roger

doi:10.1007/978-3-642-41527-2_23

Cited by 11 publications

(10 citation statements)

References 27 publications

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“…Ogierman et al [29] study medium access with adversarial jamming under the signal-to-interferenceplus-noise ratio (SINR) model. In the case of multiple channels, Dolev et al [14,15] and Gilbert et al [18], and Emek and Wattenhofer [16] examine communication problems when the adversary cannot jam all channels simultaneously, while Meier et al [26] examine the problem of node discovery.…”

Section: Related Workmentioning

confidence: 99%

(Near) optimal resource-competitive broadcast with jamming

Gilbert

King

Pettie

et al. 2014

Proceedings of the 26th ACM Symposium on Parallelism in Algorithms and Architectures

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We consider the problem of broadcasting a message from a sender to n ≥ 1 receivers in a time-slotted, single-hop, wireless network with a single communication channel. Sending and listening dominate the energy usage of small wireless devices and this is abstracted as a unit cost per time slot. A jamming adversary exists who can disrupt the channel at unit cost per time slot, and aims to prevent the transmission of the message. Let T be the number of slots jammed by the adversary. Our goal is to design algorithms whose cost is resource-competitive, that is, whose per-device cost is a function, preferably o(T ), of the adversary's cost. Devices must work with limited knowledge. The values n, T , and the adversary's jamming strategy are unknown.For 1-to-1 communication, we provide an algorithm with an expected cost of O( T ln(1/ ) + ln(1/ )), which succeeds with probability at least 1 − for any tunable parameter > 0. For 1-to-n broadcast, we provide a very different algorithm that succeeds with high probability and yields an expected cost per device of O( T /n log 4 T + log 6 n). Therefore, the bigger the system, the better advantage achieved over the adversary! We complement our upper bounds with tight or nearly tight lower bounds. We prove that any 1-to-1 communication algorithm with *

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Section: Related Workmentioning

confidence: 99%

(Near) optimal resource-competitive broadcast with jamming

Gilbert

King

Pettie

et al. 2014

Proceedings of the 26th ACM Symposium on Parallelism in Algorithms and Architectures

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“…Like [8], [7] we assume here that the receiver simultaneously listens on all frequencies. A different approach is taken in [6], [4], where the receiver listens randomly on only one frequency band at a time. The above analysis can be performed in a similar way for this situation and leads to analogous results: The capacity without common randomness shared between sender and receiver is positive if and only if the sender power exceeds the jammer power.…”

Section: Discussionmentioning

confidence: 99%

“…In each time slot, the sender chooses a subband in a random way and uses only that frequency to transmit data in that time slot. In some models [4], [6], the receiver hops over frequencies, too, and only listens to one subband at a time. The idea is that in this way, the channel will not be jammed all the time with positive probability, and some information will go through.…”

Section: Introductionmentioning

confidence: 99%

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Frequency hopping does not increase anti-jamming resilience of wireless channels

Wiese,

Papadimitratos

2015

Preprint

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The effectiveness of frequency hopping for antijamming protection of wireless channels is analyzed from an information-theoretic perspective. The sender can input its symbols into one of several frequency subbands at a time. Each subband channel is modeled as an additive noise channel. No common randomness between sender and receiver is assumed. It is shown that capacity is positive, and then equals the common randomness assisted (CR) capacity, if and only if the sender power strictly exceeds the jammer power. Thus compared to transmission over any fixed frequency subband, frequency hopping is not more resilient towards jamming, but it does increase the capacity. Upper and lower bounds on the CR capacity are provided.

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“…Recently, Dolev et al [26] consider wireless synchronization in the presence of a jamming adversary. Emek and Wattenhofer [31] examine the effectiveness of frequency hopping against an adversary who jams a strict subset of the available channels.…”

Section: Related Work On Tolerating Jamming Attacksmentioning

confidence: 99%

A resource-competitive jamming defense

King

Pettie

Saia³

et al. 2017

Distrib. Comput.

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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 resourcecompetitive analysis where the cost to correct network devices (i.e., Alice and Bob) is parameterized by the cost to 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 ϕ−1 + 1) = O(T .62 + 1) in expectation, where ϕ = (1 + √ 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. *

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Frequency Hopping against a Powerful Adversary

Cited by 11 publications

References 27 publications

(Near) optimal resource-competitive broadcast with jamming

(Near) optimal resource-competitive broadcast with jamming

Frequency hopping does not increase anti-jamming resilience of wireless channels

A resource-competitive jamming defense

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