Lecture notes in computer sciences; 218 on Advances in cryptology---CRYPTO 85
SAC '99 Proceedings of the 6th Annual International Workshop on Selected Areas in Cryptography
CRYPTO '99 Proceedings of the 19th Annual International Cryptology Conference on Advances in Cryptology
Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems
CRYPTO '96 Proceedings of the 16th Annual International Cryptology Conference on Advances in Cryptology
A Practical Approach to Identifying Storage and Timing Channels: Twenty Years Later
ACSAC '02 Proceedings of the 18th Annual Computer Security Applications Conference
The M5 Simulator: Modeling Networked Systems
IEEE Micro
Searching for resource-efficient programs: low-power pseudorandom number generators
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Multi-objective Improvement of Software Using Co-evolution and Smart Seeding
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
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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.