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

Abstract

These methods, however, have two limitations. First, the communication cost for network construction is considerably high. Second, they do not support data integrity. There are two methods for supporting data integrity, iCPDA and iPDA. But they have high communication cost due to additional integrity checking messages. To resolve this problem, we propose a novel Hilbert-curve based data aggregation scheme that enforces data privacy and data integrity for WSNs. To minimize communication cost, we utilize a tree-based network structure for constructing networks and aggregating data. To preserve data privacy, we make use of both a seed exchange algorithm and Hilbert-curve based data encryption. To support data integrity, we use an integrity checking algorithm based on the PIR technique by directly communicating between parent and child nodes. Finally, through a performance analysis, we show that our scheme outperforms the existing methods in terms of both energy efficiency and privacy preservation.

PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

“…An analytical comparison between PAgIoT, HDA [25] and iCPDA [26] is performed herein. The last two proposals have been chosen for being the ones whose security requirements are similar to those set for PAgIoT (see Section 6).…”

“…In sum, considering that PAIoT outperforms iCPDA in all cases, it can also be considered a better alternative than HDA because no messages are required for aggregation verification and just one key is managed. [25], iCPDA [26] and PAgIoT , where n is the amount of nodes.…”

“…Privacy preservation against observers is considered in [2,3,5,7,8,29,26,44,31,41,42,46,36,25,48]. The use of cryptography is demanding to manage this issue [2,3,5,7,8,28,29,26,38,46,36,25,48], as well as randomized arrays or negative surveys [44].…”

“…The use of cryptography is demanding to manage this issue [2,3,5,7,8,28,29,26,38,46,36,25,48], as well as randomized arrays or negative surveys [44].…”

“…A different approach is taken in [39], collusion is avoided by trusting users whose values are aggregated. Conversely, in [25] authors mention the protection against collusion but it is not particularly described how it is managed.…”