On the complexity of verifiable secret sharing and multiparty computation
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Secure multi-party computation problems and their applications: a review and open problems
Proceedings of the 2001 workshop on New security paradigms
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
A key-management scheme for distributed sensor networks
Proceedings of the 9th ACM conference on Computer and communications security
Cryptographic techniques for privacy-preserving data mining
ACM SIGKDD Explorations Newsletter
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Impact of Network Density on Data Aggregation in Wireless Sensor Networks
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Cache-and-query for wide area sensor databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Establishing pairwise keys in distributed sensor networks
Proceedings of the 10th ACM conference on Computer and communications security
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
SIA: secure information aggregation in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Rational secret sharing and multiparty computation: extended abstract
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Resilient aggregation in sensor networks
Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks
A wireless sensor network For structural monitoring
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
E.cient Aggregation of encrypted data in Wireless Sensor Networks
MOBIQUITOUS '05 Proceedings of the The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services
SDAP: a secure hop-by-Hop data aggregation protocol for sensor networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Underground structure monitoring with wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Rumor Riding: Anonymizing Unstructured Peer-to-Peer Systems
ICNP '06 Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Towards a theory for privacy preserving distributed OLAP
Proceedings of the 2012 Joint EDBT/ICDT Workshops
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Providing efficient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this article, we present two privacy-preserving data aggregation schemes for additive aggregation functions, which can be extended to approximate MAX/MIN aggregation functions. The first scheme---Cluster-based Private Data Aggregation (CPDA)---leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The second scheme---Slice-Mix-AggRegaTe (SMART)---builds on slicing techniques and the associative property of addition. It has the advantage of incurring less computation overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We assess the two schemes by privacy-preservation efficacy, communication overhead, and data aggregation accuracy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme (TAG), where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes.