Inferring Private Information in Wireless Sensor Networks

Daniel A. Burbano-L, Jemin George, Randy A Freeman, Kevin M Lynch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In wireless sensor networks, estimating a global parameter from locally obtained measurements via local interactions is known as the distributed parameter estimation problem. Solving these problems often require the deployment of distributed optimization algorithms that rely on a constant exchange of information among the sensor nodes. This makes such distributed algorithms vulnerable to attackers or malicious nodes that want to gain access to private information regarding the network. Based on the sliding mode control scheme, here we present a novel approach to infer sensitive information (e.g., gradient or private parameters of the local objective function) regarding a node of interest by intercepting the communication between the nodes. The effectiveness of the proposed approach is illustrated in a representative example of distributed event localization using an acoustic sensor network.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4310-4314
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 1 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: May 12 2019May 17 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
CountryUnited Kingdom
CityBrighton
Period5/12/195/17/19

Fingerprint

Sliding mode control
Sensor nodes
Parallel algorithms
Parameter estimation
Sensor networks
Wireless sensor networks
Acoustics
Communication

Keywords

  • Distributed parameter estimation
  • distributed optimization
  • sliding control
  • wireless sensor network

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Burbano-L, D. A., George, J., Freeman, R. A., & Lynch, K. M. (2019). Inferring Private Information in Wireless Sensor Networks. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 4310-4314). [8683597] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2019.8683597
Burbano-L, Daniel A. ; George, Jemin ; Freeman, Randy A ; Lynch, Kevin M. / Inferring Private Information in Wireless Sensor Networks. 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 4310-4314 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
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Burbano-L, DA, George, J, Freeman, RA & Lynch, KM 2019, Inferring Private Information in Wireless Sensor Networks. in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings., 8683597, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., pp. 4310-4314, 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, Brighton, United Kingdom, 5/12/19. https://doi.org/10.1109/ICASSP.2019.8683597

Inferring Private Information in Wireless Sensor Networks. / Burbano-L, Daniel A.; George, Jemin; Freeman, Randy A; Lynch, Kevin M.

2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4310-4314 8683597 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - In wireless sensor networks, estimating a global parameter from locally obtained measurements via local interactions is known as the distributed parameter estimation problem. Solving these problems often require the deployment of distributed optimization algorithms that rely on a constant exchange of information among the sensor nodes. This makes such distributed algorithms vulnerable to attackers or malicious nodes that want to gain access to private information regarding the network. Based on the sliding mode control scheme, here we present a novel approach to infer sensitive information (e.g., gradient or private parameters of the local objective function) regarding a node of interest by intercepting the communication between the nodes. The effectiveness of the proposed approach is illustrated in a representative example of distributed event localization using an acoustic sensor network.

AB - In wireless sensor networks, estimating a global parameter from locally obtained measurements via local interactions is known as the distributed parameter estimation problem. Solving these problems often require the deployment of distributed optimization algorithms that rely on a constant exchange of information among the sensor nodes. This makes such distributed algorithms vulnerable to attackers or malicious nodes that want to gain access to private information regarding the network. Based on the sliding mode control scheme, here we present a novel approach to infer sensitive information (e.g., gradient or private parameters of the local objective function) regarding a node of interest by intercepting the communication between the nodes. The effectiveness of the proposed approach is illustrated in a representative example of distributed event localization using an acoustic sensor network.

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KW - distributed optimization

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Burbano-L DA, George J, Freeman RA, Lynch KM. Inferring Private Information in Wireless Sensor Networks. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4310-4314. 8683597. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2019.8683597