Quantifying Interference-Assisted Signal Strength Surveillance of Sound Vibrations

Abrar, Alemayehu Solomon; Patwari, Neal; Kasera, Sneha Kumar

doi:10.1109/tifs.2020.3045316

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Cited by 4 publications

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“…Similarly, Abrar et.al. [2] contributes a CRLB on an attacker's monitoring performance as a function of the RSS step size and sampling frequency. Similar models use change point detection statistics [20], information theory and signal processing problem [10], [14], or machine learning [1], [5].…”

Section: A Related Workmentioning

confidence: 99%

Hiding Signal Strength Interference from Outside Adversaries

Han¹,

Phillips²,

Kasera³

2021

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The presence of people can be detected by passively observing the signal strength of Wifi and related forms of communication. This paper tackles the question of how and when can this be prevented by adjustments to the transmitted signal strength, and other similar measures. The main contribution of this paper is a formal framework to analyze this problem, and the identification of several scenarios and corresponding protocols which can prevent or limit the inference from passive signal strength snooping.

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