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Improving sensor network immunity under worm attacks: a software diversity approach
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International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing table of contents
Hong Kong, Hong Kong, China
SESSION: System design and optimization table of contents
Pages 149-158  
Year of Publication: 2008
ISBN:978-1-60558-073-9
Authors
Yi Yang  The Pennsylvania State University, University Park, PA, USA
Sencun Zhu  The Pennsylvania State University, University Park, PA, USA
Guohong Cao  The Pennsylvania State University, University Park, PA, USA
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Because of cost and resource constraints, sensor nodes do not have a complicated hardware architecture or operating system to protect program safety. Hence, the notorious buffer-overflow vulnerability that has caused numerous Internet worm attacks could also be exploited to attack sensor networks. We call the malicious code that exploits a buffer-overflow vulnerability in a sensor program sensor worm. Clearly, sensor worm will be a serious threat, if not the most dangerous one, when an attacker could simply send a single packet to compromise the entire sensor network. Despite its importance, so far little work has been focused on sensor worms.

In this work, we first illustrate the feasibility of launching sensor worms through real experiments on Mica2 motes. Inspired by the survivability through heterogeneity philosophy, we then explore the technique of software diversity to combat sensor worms. Given a limited number of software versions, we design an efficient algorithm to assign the appropriate version of software to each sensor, so that sensor worms are restrained from propagation. We also examine the impact of sensor node deployment errors on worm propagation, which directs the selection of our system parameters based on percolation theory. Finally, extensive analytical and simulation results confirm the effectiveness of our scheme in containing sensor worms.


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:
Yi Yang: colleagues
Sencun Zhu: colleagues
Guohong Cao: colleagues