
TL;DR
This paper presents a layered GPU-based architecture for cryptographic applications, enabling high-throughput RSA operations and random bit generation, making secure computations more practical on affordable hardware.
Contribution
It introduces a novel three-tier trusted architecture on GPUs that integrates entropy generation and parallelized RSA cryptography, demonstrating high throughput and practicality.
Findings
GPU-based random integer generation at 32-40 GB/s
RSA encryption with 16,128-bit exponents achieved on mid-range GPUs
Proposes an accessible, high-throughput trusted cryptographic architecture
Abstract
Acceleration of cryptographic applications on massively parallel computing platforms, such as Graphics Processing Units (GPUs), becomes a real challenge as their decreasing cost and mass production makes practical implementations attractive. We propose a layered trusted architecture integrating random bits generation and parallelized RSA cryptographic computations on such platforms. The GPU-resident, three-tier, MR architecture consists of a RBG, using the GPU as a deep entropy pool; a bignum modular arithmetic library using the Residue Number System; and GPU APIs for RSA key generation, encryption and decryption. Evaluation results of an experimental OpenCL implementation show a 32-40 GB/s throughput of random integers, and encryptions with up to 16,128-bit long exponents on a commercial mid-range GPUs. This suggests an ubiquitous solution for autonomous trusted architectures combining…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsChaos-based Image/Signal Encryption · Cryptography and Residue Arithmetic · Cryptographic Implementations and Security
