Privacy‐preserving robust data aggregation in wireless sensor networks

Abstract

In-network data aggregation in wireless sensor networks (WSNs) is a technique aimed at reducing the communication overhead-sensed data are combined into partial results at intermediate nodes during message routing. However, in the above technique, some sensor nodes need to send their individual sensed values to an aggregator node, empowered with the capability to decrypt the received data to perform a partial aggregation. This scenario raises privacy concerns in applications like personal health care and the military surveillance. A few other solutions exist where the data are not disclosed to the aggregator (e.g., using privacy homomorphism (PH)), but these solutions are not robust to node or communication failure. The contributions of this paper are two-fold: first, we design a private data aggregation protocol that does not leak individual sensed values during the data aggregation process. In particular, neither the base station (BS) nor the other nodes are able to compromise the privacy of an individual node's sensed value. Second, the proposed protocol is robust to data-loss; if there is a node-failure or communication failure, the protocol is still able to compute the aggregate and to report to the base station the number of nodes that participated in the aggregation. To the best of our knowledge, our scheme is the first one that efficiently addresses the above issues all at once. Copyright © 2009 John Wiley & Sons, Ltd

Multiorder Fusion Data Privacy-Preserving Scheme for Wireless Sensor Networks

“…Data aggregation is necessary for wireless sensor networks. Based on the management pattern of cluster structure, in [1], Conti et al proposed a privacy-preserving algorithm for data fusion. In particular, neither the base station (BS) nor other nodes are able to compromise the privacy of an individual node's sensed value.…”

“…Many of the existing researches have increased the privacy protection function on the basis of data fusion. For instance, in [1], Conti et al design a private data aggregation protocol that does not leak individual sensed values during the data aggregation process. It enhances the robustness, and the node computing complexity and data transmission are not large.…”

Hilbert-Curve Based Data Aggregation Scheme to Enforce Data Privacy and Data Integrity for Wireless Sensor Networks

“…Finally, the sink node sends the aggregated data to the service client (lines 12∼15). If (the node is InternalNode){ (6) StoresencDatafrom msg; (7) decryptedData = decryption(encData)' (8) aggregatedData += decryptedData; (9) newEncData = HilbertCurve(direction, curveLevel, aggregatedData); (10) If (all data is received from childNode) (11) SendMessage(encData);to ParentNode; (12) }If (a node is SinkNode) (13) StoreencData from msg; (14) decryptedData = decryption(encData); (15) Send Message(decryptedData) to User;}} End Algorithm Algorithm 3: Data aggregation algorithm. …”

WSN Data Transmission Algorithm Based on Spatial Data Aggregation

“…The sensor nodes of the above algorithm are subject to serious losses and susceptible to environmental impacts during service. The new research worked on data aggregation based on route algorithm (Wei and Yang, 2013;Lee, Kim and Chang, 2014), but few took data security into account (Conti et al, 2009). During the calculation process, frequent encryption and decryption operations increase the overall operation time (Zhou, Yang and He, 2014;Yang et al, 2008).…”