Performance Analysis of Network Efficiency Based on Multi-Level Encryption Algorithms

Abstract

With an increasing rate of data exchange via networks rapidly, information security is a critical indicator of network effectiveness. Data transmission has to be secured, and that is crucially done through cryptography, where AES, DES, and multi-level encryption (AES+DES) are the significant methods. This research provides a comparative performance analysis of AES and DES. Execution times for encryption and decryption, efficiency ratios, and memory usage were recorded using various dataset sizes (1, 10, 100, 1,000, 10,000, and 50,000 images). Results show that AES is faster than DES in all cases with less memory. Experiments were conducted on both CPU and GPU: Results indicate that GPU acceleration does make a difference in accelerating encryption with up to a (6.68×) speedup for multi-level encryption and (8.13×) for AES with 50,000 images. GPU-memory usage was (35%) less than the respective CPU-based memory, thus being more efficient. Multi-level encryption presents a potential trade-off for more robust security, while DES is insufficient for bulk encryption because its performance is considerably lowered.