TY - GEN
T1 - KIPDA
T2 - IEEE INFOCOM 2011
AU - Groat, Michael M.
AU - Hey, Wenbo
AU - Forrest, Stephanie
PY - 2011
Y1 - 2011
N2 - When wireless sensor networks accumulate sensitive or confidential data, privacy becomes an important concern. Sensors are often resource-limited and power-constrained, and data aggregation is commonly used to address these issues. However, providing privacy without disrupting in-network data aggregation is challenging. Although privacy-preserving data aggregation for additive and multiplicative aggregation functions has been studied, nonlinear aggregation functions such as maximum and minimum have not been well addressed. We present KIPDA, a privacy-preserving aggregation method, which we specialize for maximum and minimum aggregation functions. KIPDA obfuscates sensitive measurements by hiding them among a set of camouflage values, enabling k-indistinguishability for data aggregation. In principle, KIPDA can be used to hide a wide range of aggregation functions, although this paper considers only maximum and minimum. Because the sensitive data are not encrypted, it is easily and efficiently aggregated with minimal in-network processing delay. We quantify the efficiency of KIPDA in terms of power consumption and time delay, studying tradeoffs between the protocol's effectiveness and its resilience against collusion.
AB - When wireless sensor networks accumulate sensitive or confidential data, privacy becomes an important concern. Sensors are often resource-limited and power-constrained, and data aggregation is commonly used to address these issues. However, providing privacy without disrupting in-network data aggregation is challenging. Although privacy-preserving data aggregation for additive and multiplicative aggregation functions has been studied, nonlinear aggregation functions such as maximum and minimum have not been well addressed. We present KIPDA, a privacy-preserving aggregation method, which we specialize for maximum and minimum aggregation functions. KIPDA obfuscates sensitive measurements by hiding them among a set of camouflage values, enabling k-indistinguishability for data aggregation. In principle, KIPDA can be used to hide a wide range of aggregation functions, although this paper considers only maximum and minimum. Because the sensitive data are not encrypted, it is easily and efficiently aggregated with minimal in-network processing delay. We quantify the efficiency of KIPDA in terms of power consumption and time delay, studying tradeoffs between the protocol's effectiveness and its resilience against collusion.
UR - http://www.scopus.com/inward/record.url?scp=79960854358&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960854358&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2011.5935010
DO - 10.1109/INFCOM.2011.5935010
M3 - Conference contribution
AN - SCOPUS:79960854358
SN - 9781424499212
T3 - Proceedings - IEEE INFOCOM
SP - 2024
EP - 2032
BT - 2011 Proceedings IEEE INFOCOM
Y2 - 10 April 2011 through 15 April 2011
ER -