A Comparison of Computer-Based Technologies Suitable for Cryptographic Attacks
Developed initially for tasks related to computer graphics, GPUs are increasingly being used for general purpose processing, including scientific and engineering applications. In this contribution, we have analysed the performance of three graphics cards that belong to the parallel computing CUDA platform with two C++ and Java multi-threading implementations, using as an example of computation a brute-force attack on KeeLoq, one of the best known remote keyless entry applications. As it was expected, these implementations are not able to break algorithms with 64-bit keys, but the results allow us to provide valuable information regarding the compared capabilities of the tested platforms.
KeywordsCryptography CUDA C++ Encryption Java OpenMP
This work has been supported by the European Union FEDER funds distributed through Ministerio de Economía y Competitividad (Spain) under the project TIN2014-55325-C2-1-R (ProCriCiS), and through Comunidad de Madrid (Spain) under the project S2013/ICE-3095-CM (CIBERDINE).
- 1.Kasper, T.: Security Analysis of Pervasive Wireless Devices - Physical and Protocol Attacks in Practice Ruhr-University Bochum, Germany (2011)Google Scholar
- 2.Eisenbarth, T., Kasper, T., Moradi, A., Paar, C., Salmasizadeh, M., Shalmani, M.T.M.: Physical cryptoanalysis of KeeLoq code hopping applications. Cryptology ePrint Archive, Report 2008/058, pp. 1–22 (2008). https://eprint.iacr.org/2008/058.pdf
- 3.Corp, N.: What is GPU computing? (2016). https://www.nvidia.com/object/what-is-gpu-computing.html
- 5.NVIDIA Corporation: Programming Guide (2016). http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities
- 6.Oracle Corporation: Executors (Java Platform SE 8) (2016). https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/Executors.html
- 7.Oracle Corporation: Executor Service (Java Platform SE 8) (2016). https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/ExecutorService.html
- 8.NVIDIA Corporation: CUDA Legacy GPUs (2016). https://developer.nvidia.com/cuda-legacy-gpus
- 9.NVIDIA Corporation: Tesla P100 (2016). http://www.nvidia.com/object/tesla-p100.html
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.