An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks

Sencun Zhu, Sanjeev Setia, Sushil Jajodia, Peng Ning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

398 Scopus citations

Abstract

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects false data into the network with the goal of deceiving the base station or depleting the resources of the relaying nodes. Standard authentication mechanisms cannot prevent this attack if the adversary has compromised one or a small number of sensor nodes. In this paper, we present an interleaved hop-by-hop authentication scheme that guarantees that the base station will detect any injected false data packets when no more than a certain number t nodes are compromised. Further, our scheme provides an upper bound B for the number of hops that a false data packet could be forwarded before it is detected and dropped, given that there are up to t colluding compromised nodes. We show that in the worst case B is O(t 2). Through performance analysis, we show that our scheme is efficient with respect to the security it provides, and it also allows a tradeoff between security and performance.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Symposium on Security and Privacy
Pages259-271
Number of pages13
StatePublished - Aug 16 2004
EventProceedings - 2004 IEEE Symposium on Security and Privacy - Berkeley, CA, United States
Duration: May 9 2004May 12 2004

Publication series

NameProceedings - IEEE Symposium on Security and Privacy
Volume2004

Other

OtherProceedings - 2004 IEEE Symposium on Security and Privacy
Country/TerritoryUnited States
CityBerkeley, CA
Period5/9/045/12/04

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint

Dive into the research topics of 'An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks'. Together they form a unique fingerprint.

Cite this