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 language | English (US) |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4310-4314 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479981311 |
| DOIs | |
| State | Published - May 1 2019 |
| Event | 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom Duration: May 12 2019 → May 17 2019 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 2019-May |
| ISSN (Print) | 1520-6149 |
Conference
| Conference | 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 |
|---|---|
| Country | United Kingdom |
| City | Brighton |
| Period | 5/12/19 → 5/17/19 |
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Keywords
- Distributed parameter estimation
- distributed optimization
- sliding control
- wireless sensor network
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
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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 proceeding › Conference contribution
TY - GEN
T1 - Inferring Private Information in Wireless Sensor Networks
AU - Burbano-L, Daniel A.
AU - George, Jemin
AU - Freeman, Randy A
AU - Lynch, Kevin M
PY - 2019/5/1
Y1 - 2019/5/1
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.
KW - Distributed parameter estimation
KW - distributed optimization
KW - sliding control
KW - wireless sensor network
UR - http://www.scopus.com/inward/record.url?scp=85069001872&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069001872&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2019.8683597
DO - 10.1109/ICASSP.2019.8683597
M3 - Conference contribution
AN - SCOPUS:85069001872
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 4310
EP - 4314
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -