Evolutionary Design of Message Efficient Secrecy Amplification Protocols

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.

[1]  Virgil D. Gligor,et al.  A key-management scheme for distributed sensor networks , 2002, CCS '02.

[2]  Petr Svenda,et al.  Authenticated key exchange with group support for wireless sensor networks , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[3]  Petr Svenda,et al.  Evolutionary design of secrecy amplification protocols for wireless sensor networks , 2009, WiSec '09.

[4]  Alan Bundy,et al.  Constructing Induction Rules for Deductive Synthesis Proofs , 2006, CLASE.

[5]  David P. Anderson,et al.  BOINC: a system for public-resource computing and storage , 2004, Fifth IEEE/ACM International Workshop on Grid Computing.

[6]  Dong Hoon Lee,et al.  A Key Management Scheme for Commodity Sensor Networks , 2005, ADHOC-NOW.

[7]  Ross J. Anderson,et al.  Key infection: smart trust for smart dust , 2004, Proceedings of the 12th IEEE International Conference on Network Protocols, 2004. ICNP 2004..

[8]  Petr Svenda,et al.  Smart Dust Security - Key Infection Revisited , 2006, STM.

[9]  Giovanni Squillero,et al.  An Effective Technique for Minimizing the Cost of Processor Software-Based Diagnosis in SoCs , 2006, Proceedings of the Design Automation & Test in Europe Conference.

[10]  W. Banzhaf,et al.  1 Linear Genetic Programming , 2007 .