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SMOLKA, T. ŠVENDA, P. SEKANINA, L. MATYÁŠ, V.
Original Title
Evolutionary Design of Message Efficient Secrecy Amplification Protocols
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Secrecy amplification protocols are mechanisms that can significantly improve security of partially compromised wireless sensor networks (e.g., turning a half-compromised network into the 95% secure one). The main disadvantage of existing protocols is a high communication overhead increasing exponentially with network density. We devise a novel family of these protocols exhibiting only a linear increase of the communication overhead. The protocols are automatically generated by linear genetic programming (LGP) connected to a network simulator. After a deep analysis of various characteristics of this new family of protocols, with a special focus on the tuning of LGP parameters, new and better group-oriented protocols are discovered by LGP. A multi-criteria optimization is then utilized to further reduce the communication overhead down to 1/2 of the original amount while maintaining the original fraction of secure links.
Keywords
linear genetic programming, wireless sensor network, security
Authors
SMOLKA, T.; ŠVENDA, P.; SEKANINA, L.; MATYÁŠ, V.
RIV year
2012
Released
25. 1. 2012
Publisher
Springer Verlag
Location
Heidelberg
ISBN
978-3-642-29138-8
Book
Proc. of the 15th European Conference on Genetic Programming
Edition
Lecture Notes in Computer Science
Pages from
194
Pages to
205
Pages count
12
URL
https://www.fit.vut.cz/research/publication/9872/
BibTex
@inproceedings{BUT91463, author="Tobiáš {Smolka} and Petr {Švenda} and Lukáš {Sekanina} and Václav {Matyáš}", title="Evolutionary Design of Message Efficient Secrecy Amplification Protocols", booktitle="Proc. of the 15th European Conference on Genetic Programming", year="2012", series="Lecture Notes in Computer Science", volume="7244", pages="194--205", publisher="Springer Verlag", address="Heidelberg", doi="10.1007/978-3-642-29139-5\{_}17", isbn="978-3-642-29138-8", url="https://www.fit.vut.cz/research/publication/9872/" }