Abstract
Wireless sensor networks (WSNs) are omnipresent in a multitude of applications. One of the important common requirements of these applications is the data security. Indeed, the exchanged data in WSNs are often considered as a preferred target, which can be a subject of several threats, such as eavesdropping, replay, falsification, alteration, etc. Another important common requirement of WSNs applications is data aggregation. Indeed, the limitations of such networks in terms of energy, bandwidth and storage accentuate the need of data aggregation. In this paper, we address these two issues. We propose a new efficient approach for data integrity and credibility protection for WSNs, while ensuring the data aggregation. We consider a cluster-based network architecture, where sensor nodes are equally distributed in clusters. Each sensor node is in charge to deliver one bit of the sensed data and at the same time observe the remaining parts through a parity control based encryption approach. In this manner, the sensed data could be effectively and securely controlled with a low overhead compared to the classical aggregation approaches, where all the nodes transmit individually the sensed data. To validate the proposed protocol we have simulated it using the simulator CupCarbon and in order to evaluate its efficiency in terms of energy, we have developed a prototype with the TelosB platform, where the obtained results show that our method is less energy consuming.1
| Original language | English |
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| Title of host publication | 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 432-437 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509004805 |
| DOIs | |
| State | Published - 28 Jan 2016 |
| Externally published | Yes |
Publication series
| Name | 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015 |
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Bibliographical note
Publisher Copyright:© 2015 IEEE.
ASJC Scopus subject areas
- Signal Processing