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Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems

Research output: Contribution to journalLetter

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Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems. / Fafoutis, Xenofon; Marchegiani, Letizia; Papadopoulos, Georgios Z.; Piechocki, Robert; Tryfonas, Theo; Oikonomou, George.

In: IEEE Signal Processing Letters, Vol. 24, No. 2, 02.2017, p. 136-140.

Research output: Contribution to journalLetter

Harvard

Fafoutis, X, Marchegiani, L, Papadopoulos, GZ, Piechocki, R, Tryfonas, T & Oikonomou, G 2017, 'Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems', IEEE Signal Processing Letters, vol. 24, no. 2, pp. 136-140. https://doi.org/10.1109/LSP.2016.2642300

APA

Vancouver

Author

Fafoutis, Xenofon ; Marchegiani, Letizia ; Papadopoulos, Georgios Z. ; Piechocki, Robert ; Tryfonas, Theo ; Oikonomou, George. / Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems. In: IEEE Signal Processing Letters. 2017 ; Vol. 24, No. 2. pp. 136-140.

Bibtex

@article{4394b8d7d8fb4c6ea91e06fb9cab6c30,
title = "Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems",
abstract = "With the ubiquity of sensing technologies in our personal spaces, the protection of our privacy and the confidentiality of sensitive data becomes a major concern. In this paper, we focus on wearable embedded systems that communicate data periodically over the wireless medium. In this context, we demonstrate that private information about the physical activity levels of the wearer can leak to an eavesdropper through the physical layer. Indeed, we show that the physical activity levels strongly correlate with changes in the wireless channel that can be captured by measuring the signal strength of the eavesdropped frames. We practically validate this correlation in several scenarios in a real residential environment, using data collected by our prototype wearable accelerometer-based sensor. Lastly, we propose a privacy enhancement algorithm thatmitigates the leakage of this private information.",
author = "Xenofon Fafoutis and Letizia Marchegiani and Papadopoulos, {Georgios Z.} and Robert Piechocki and Theo Tryfonas and George Oikonomou",
year = "2017",
month = "2",
doi = "10.1109/LSP.2016.2642300",
language = "English",
volume = "24",
pages = "136--140",
journal = "IEEE Signal Processing Letters",
issn = "1070-9908",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
number = "2",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems

AU - Fafoutis, Xenofon

AU - Marchegiani, Letizia

AU - Papadopoulos, Georgios Z.

AU - Piechocki, Robert

AU - Tryfonas, Theo

AU - Oikonomou, George

PY - 2017/2

Y1 - 2017/2

N2 - With the ubiquity of sensing technologies in our personal spaces, the protection of our privacy and the confidentiality of sensitive data becomes a major concern. In this paper, we focus on wearable embedded systems that communicate data periodically over the wireless medium. In this context, we demonstrate that private information about the physical activity levels of the wearer can leak to an eavesdropper through the physical layer. Indeed, we show that the physical activity levels strongly correlate with changes in the wireless channel that can be captured by measuring the signal strength of the eavesdropped frames. We practically validate this correlation in several scenarios in a real residential environment, using data collected by our prototype wearable accelerometer-based sensor. Lastly, we propose a privacy enhancement algorithm thatmitigates the leakage of this private information.

AB - With the ubiquity of sensing technologies in our personal spaces, the protection of our privacy and the confidentiality of sensitive data becomes a major concern. In this paper, we focus on wearable embedded systems that communicate data periodically over the wireless medium. In this context, we demonstrate that private information about the physical activity levels of the wearer can leak to an eavesdropper through the physical layer. Indeed, we show that the physical activity levels strongly correlate with changes in the wireless channel that can be captured by measuring the signal strength of the eavesdropped frames. We practically validate this correlation in several scenarios in a real residential environment, using data collected by our prototype wearable accelerometer-based sensor. Lastly, we propose a privacy enhancement algorithm thatmitigates the leakage of this private information.

U2 - 10.1109/LSP.2016.2642300

DO - 10.1109/LSP.2016.2642300

M3 - Letter

VL - 24

SP - 136

EP - 140

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

SN - 1070-9908

IS - 2

ER -