| Title | Efficient Implementation of McEliece Cryptosystem on Graphic Processing Unit |
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Elsobky, Alaa Mahmoud, Farag, Abdelalim Kamal, Keshk, Arabi |
| Conference Name | Proceedings of the 10th International Conference on Informatics and Systems |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4062-5 |
| Keywords | attack vectors, GPU, Human Behavior, Local-memory, McEliece Cryptosystem, openCL, pubcrawl, resilience, Scalability |
| Abstract | McEliece is a public-key cryptosystem based on error correcting codes. It has the ability to resist quantum-computer attacks which can break different modern public key cryptosystems such as RSA. Further more, it's encryption and decryption are very fast and have good characteristics for data parallel processing. Nowadays, modern graphic processing units (GPUs) are available in almost all hardware platforms. GPUs can comprise many compute cores which can process a huge data in parallel. In this paper, different implementations of McEliece cryptosystem are explored on NVIDIA GTX780 GPU using OpenCL framework. Our implementation results show that GPU is 331x faster than CPU when apply local memory with vector data-type to encrypt 216 messages. |
| URL | http://doi.acm.org/10.1145/2908446.2908491 |
| DOI | 10.1145/2908446.2908491 |
| Citation Key | elsobky_efficient_2016 |
Efficient Implementation of McEliece Cryptosystem on Graphic Processing Unit