Cobra: Correlation-Based Content Authentication in Wireless Sensor Networks

The energy-constrained wireless sensor nodes require the designs of energy-efficient content authentication protocols. In this paper, we combine the approaches of cryptography and content analysis to propose a new light-weight content authentication framework Cobra. In Cobra, only a small fraction of transmitted packets are protected with signatures. The unprotected packets are authenticated using the contents of the protected packets and a pre-learned correlation model. Cobra is resilient to four common types of data integrity attacks. Both our theoretical analysis and the experimental results show that Cobra offers high detection rate against aggressive attacks. Compared to three competing methods, it reduces the average data error by up to 60% and the security overhead by an order of one magnitude. As the attacks become more aggressive, Cobra´s average data error is almost unaffected whereas the average data errors of the competing methods all grow linearly.