6th International ICST Symposium on Modeling and Optimization

Research Article

ABBA: A Balls and Bins Approach to Secure Aggregation in WSNs

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  • @INPROCEEDINGS{10.4108/ICST.WIOPT2008.3183,
        author={Claude Castelluccia and Claudio Soriente},
        title={ABBA: A Balls and Bins Approach to Secure Aggregation in WSNs},
        proceedings={6th International ICST Symposium on Modeling and Optimization},
        publisher={IEEE},
        proceedings_a={WIOPT},
        year={2008},
        month={8},
        keywords={Data aggregation Privacy Integrity.},
        doi={10.4108/ICST.WIOPT2008.3183}
    }
    
  • Claude Castelluccia
    Claudio Soriente
    Year: 2008
    ABBA: A Balls and Bins Approach to Secure Aggregation in WSNs
    WIOPT
    IEEE
    DOI: 10.4108/ICST.WIOPT2008.3183
Claude Castelluccia1,*, Claudio Soriente2,*
  • 1: INRIA 655, avenue de l’Europe, 38334 Saint-Ismier Cedex, France.
  • 2: Computer Science Department, University of California, Irvine
*Contact email: Claude.Castelluccia@inrialpes.fr, csorient@uci.edu

Abstract

Sensor networks pledge to solve many monitoring problems: thousands of small inexpensive devices can be easily deployed in any environment and can provide measurements about diverse phenomenons, such as temperature, pollution, birds migration, etc. As sensors are low-capabilities, battery powered devices, several protocols have been proposed to maximize their lifetime, but only recently research has focused on security issues such as privacy and integrity: sensors are also very easy to tamper with and usually deployed in hostile environments, where they can be easily corrupted by an attacker in order to manipulate the information provided by the network. In this paper, we present a novel secure data aggregation protocol that provides security and integrity for sensor networks using inexpensive cryptographic tools. Our scheme protects against both internal and external attackers and balances message size, as well as energy consumption among network nodes. It provides the sink with a great amount of information, as it is able to compute mean, standard deviation, frequency distribution, etc. of the sensed values, with only one query.