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Attack-resilient hierarchical data aggregation in sensor networks
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Source Workshop on Security of ad hoc and Sensor Networks archive
Proceedings of the fourth ACM workshop on Security of ad hoc and sensor networks table of contents
Alexandria, Virginia, USA
SESSION: Secure data aggregation and transmission table of contents
Pages: 71 - 82  
Year of Publication: 2006
ISBN:1-59593-554-1
Authors
Sankardas Roy  George Mason University
Sanjeev Setia  George Mason University
Sushil Jajodia  George Mason University
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

In a large sensor network, in-network data aggregation, i.e., combining partial results at intermediate nodes during message routing, significantly reduces the amount of communication and hence the energy consumed. Recently several researchers have proposed robust aggregation frameworks, which combine multi-path routing schemes with duplicate-insensitive algorithms, to accurately compute aggregates (e.g., Sum, Count, Average) in spite of message losses resulting from node and transmission failures. However, these aggregation frameworks have been designed without security in mind. Given the lack of hardware support for tamper-resistance and the unattended nature of sensor nodes, sensor networks are highly vulnerable to node compromises. We show that even if a few compromised nodes contribute false sub-aggregate values, this results in large errors in the aggregate computed at the root of the hierarchy. We present modifications to the aggregation algorithms that guard against such attacks, i.e., we present algorithms for resilient hierarchical data aggregation despite the presence of compromised nodes in the aggregation hierarchy. We evaluate the performance and costs of our approach via both analysis and simulation. Our results show that our approach is scalable and efficient.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Sankardas Roy: colleagues
Sanjeev Setia: colleagues
Sushil Jajodia: colleagues