Abstract
In previous work, we have demonstrated that it is possible to use Genetic Programming to minimise the resource consumption of software, such as its power consumption or execution time. In this paper, we investigate the extent to which Genetic Programming can be used to gain fine-grained control over software timing. We introduce the ideas behind our work, and carry out experimentation to find that Genetic Programming is indeed able to produce software with unusual and desirable timing properties, where it is not obvious how a manual approach could replicate such results. In general, we discover that Genetic Programming is most effective in controlling statistical properties of software rather than precise control over its timing for individual inputs. This control may find useful application in cryptography and embedded systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
White, D.R.: Searching for resource-efficient programs: Low-power pseudorandom number generators. In: GECCO 2008: Proceedings of the 10th annual conference on Genetic and evolutionary computation (2008)
Arcuri, A., White, D.R., Clark, J., Yao, X.: Multi-objective improvement of software using co-evolution and smart seeding. In: International Conference on Simulated Evolution And Learning (SEAL), pp. 61–70 (2008)
ECJ: Evolutionary computation in Java, http://www.cs.gmu.edu/~eclab/projects/ecj/
Binkert, N.L., Dreslinski, R.G., Hsu, L.R., Lim, K.T., Saidi, A.G., Reinhardt, S.K.: The M5 simulator: Modeling networked systems. IEEE Micro 26(4), 52–60 (2006)
Webster, A.F., Tavares, S.E.: On the design of s-boxes. In: Williams, H.C. (ed.) CRYPTO 1985. LNCS, vol. 218, pp. 523–534. Springer, Heidelberg (1986)
Kelsey, J., Schneier, B., Ferguson, N.: Yarrow-160: Notes on the design and analysis of the yarrow cryptographic pseudorandom number generator. In: Heys, H.M., Adams, C.M. (eds.) SAC 1999. LNCS, vol. 1758, pp. 13–33. Springer, Heidelberg (2000)
Kocher, P.C.: Timing attacks on implementations of diffie-hellman, rsa, dss, and other systems. In: Koblitz, N. (ed.) CRYPTO 1996. LNCS, vol. 1109, pp. 104–113. Springer, Heidelberg (1996)
Kocher, P., Jaffe, J., Jun, B.: Differential power analysis, pp. 388–397. Springer, Heidelberg (1999)
Kemmerer, R.A.: A practical approach to identifying storage and timing channels: Twenty years later. In: Computer Security Applications Conference, p. 109 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
White, D.R., Tapiador, J.M.E., Hernandez-Castro, J.C., Clark, J.A. (2010). Fine-Grained Timing Using Genetic Programming. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds) Genetic Programming. EuroGP 2010. Lecture Notes in Computer Science, vol 6021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12148-7_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-12148-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12147-0
Online ISBN: 978-3-642-12148-7
eBook Packages: Computer ScienceComputer Science (R0)