Optimized Hybrid Central Processing Unit–Graphics Processing Unit Workflow for Accelerating Advanced Encryption Standard Encryption: Performance Evaluation and Computational Modeling
Source abstract
Abstract
This study addresses the growing demand for scalable data encryption by evaluating the performance of AES (Advanced Encryption Standard) encryption and decryption using CBC (Cipher Block Chaining) and CTR (Counter Mode) modes across various CPU (Central Processing Unit) and GPU (Graphics Processing Unit) hardware models. The objective is to highlight GPU acceleration benefits and propose an optimized hybrid CPU–GPU workflow for large-scale data security. Methods include benchmarking encryption performance with provided data, mathematical models, and computational analysis. The results indicate significant performance gains with GPU acceleration, particularly for large datasets, and demonstrate that the hybrid CPU–GPU approach balances speed and resource utilization efficiently.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Data Storage Technologies · Cryptography and Data Security · Cryptographic Implementations and Security
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Division of Artificial Intelligence Convergence Engineering, Sahmyook University, Seoul 01795, Republic of Korea
Funding
Korean government (MSIT)
References (30)
Show source-provided references
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