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Reputation-based framework for high integrity sensor networks (2004)
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| Venue: | In SASN ’04: Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks |
| Citations: | 245 - 7 self |
BibTeX
@INPROCEEDINGS{Ganeriwal04reputation-basedframework,
author = {Saurabh Ganeriwal and Mani B. Srivastava},
title = {Reputation-based framework for high integrity sensor networks},
booktitle = {In SASN ’04: Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks},
year = {2004},
pages = {66--77},
publisher = {ACM Press}
}
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Abstract
The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes. We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes. We are currently developing a system within this framework where we employ a Bayesian formulation, specifically a beta reputation system, for reputation representation, updates and integration. We will explain the reasoning behind our design choices, analyzing their pros & cons. We conclude the paper by verifying the efficacy of this system through some preliminary simulation results.
Keyphrases
reputation-based framework high integrity sensor network sensor network faulty node unique characteristic cryptography cannot prevent conventional view design choice internal adversary network security novel misbehavior reputation representation generalized approach non-malicious insertion beta reputation system trustworthy sensor network data analysis different domain bayesian formulation preliminary simulation result pro con general tool traditional approach
