Securely computing an approximate median in wireless sensor networks

Wireless Sensor Networks (WSNs) have proven to be useful in many applications, such as military surveillance and environment monitoring. To meet the severe energy constraints in WSNs, some researchers have proposed to use the in-network data aggregation technique (i.e., combining partial results at intermediate nodes during message routing), which significantly reduces the communication overhead. Given the lack of hardware support for tamper resistance and the unattended nature of sensor nodes, sensor network protocols need to be designed with security in mind. Recently, researchers proposed algorithms for securely computing a few aggregates, such as Sum (the sum of the sensed values), Count (number of nodes) and Average. However, to the best of our knowledge, there is no prior work which securely computes the Median, although the Median is considered to be an important aggregate. The contribution of this paper is twofold. We first propose a protocol to compute an approximate Median and verify if it has been falsified by an adversary. Then, we design an attack-resilient algorithm to compute the Median even in the presence of a few compromised nodes. We evaluate the performance and cost of our approach via both analysis and simulation. Our results show that our approach is scalable and efficient.

[1]  Ralph C. Merkle,et al.  A Digital Signature Based on a Conventional Encryption Function , 1987, CRYPTO.

[2]  Keith B. Frikken,et al.  An efficient integrity-preserving scheme for hierarchical sensor aggregation , 2008, WiSec '08.

[3]  Jeffrey Considine,et al.  Approximate aggregation techniques for sensor databases , 2004, Proceedings. 20th International Conference on Data Engineering.

[4]  Sencun Zhu,et al.  SDAP: a secure hop-by-Hop data aggregation protocol for sensor networks , 2006, MobiHoc '06.

[5]  Srinivasan Seshan,et al.  Synopsis diffusion for robust aggregation in sensor networks , 2004, SenSys '04.

[6]  Sanjeev Khanna,et al.  Power-conserving computation of order-statistics over sensor networks , 2004, PODS '04.

[7]  Bruce G. Lindsay,et al.  Approximate medians and other quantiles in one pass and with limited memory , 1998, SIGMOD '98.

[8]  David A. Wagner,et al.  Resilient aggregation in sensor networks , 2004, SASN '04.

[9]  Graham Cormode,et al.  An improved data stream summary: the count-min sketch and its applications , 2004, J. Algorithms.

[10]  Sasikanth Avancha,et al.  Security for Sensor Networks , 2004 .

[11]  Dawn Xiaodong Song,et al.  Secure hierarchical in-network aggregation in sensor networks , 2006, CCS '06.

[12]  Peter J. Haas,et al.  Improved histograms for selectivity estimation of range predicates , 1996, SIGMOD '96.

[13]  Imrich Chlamtac,et al.  The P2 algorithm for dynamic calculation of quantiles and histograms without storing observations , 1985, CACM.

[14]  William J. Mackinnon,et al.  Table for Both the Sign Test and Distribution-Free Confidence Intervals of the Median for Sample Sizes to 1,000 , 1964 .

[15]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[16]  Sanjeev Khanna,et al.  Space-efficient online computation of quantile summaries , 2001, SIGMOD '01.

[17]  J. Ian Munro,et al.  Selection and sorting with limited storage , 1978, 19th Annual Symposium on Foundations of Computer Science (sfcs 1978).

[18]  Sushil Jajodia,et al.  Attack-resilient hierarchical data aggregation in sensor networks , 2006, SASN '06.

[19]  Divyakant Agrawal,et al.  Medians and beyond: new aggregation techniques for sensor networks , 2004, SenSys '04.

[20]  Peter J. Haas,et al.  The New Jersey Data Reduction Report , 1997 .

[21]  Levente Buttyán,et al.  RANBAR: RANSAC-based resilient aggregation in sensor networks , 2006, SASN '06.

[22]  Boaz Patt-Shamir A note on efficient aggregate queries in sensor networks , 2004, PODC '04.

[23]  David Sun,et al.  COUGAR: the network is the database , 2002, SIGMOD '02.