Experimental Evaluation of the Performance and Security of the ChaCha20 Stream Cipher Using Python

Authors

  • Abdulsamad Ibrahim Department of basic Science Dentistry, College of Dentistry, Hawler Medical University, Erbil 44001, Iraq

DOI:

https://doi.org/10.70917/ijcisim-2026-5838

Keywords:

ChaCha20, Stream Cipher, Encryption, Avalanche Effect, Key Sensitivity, Cryptographic

Abstract

In this new digital age, security and integrity of data have become crucial especially in real-time applications and environments where resources are limited. This study introduces a performance and security analysis of the ChaCha20 stream cipher using a Python-based implementation of the algorithm. Encryption and decryption time, avalanche effect, key sensitivity, decryption success rate, ciphertext byte distribution are the evaluation metrics. Experiments were done with plaintext sizes from 64 to 2048 bytes. The results show that ChaCha20 has very low encryption and decryption times which verified the high efficiency and scalability. The avalanche effect although does decrease slightly with the size of plaintext, maintains enough diffusion to fight against differential cryptanalysis. Key sensitivity is consistently close to 50%, and decryption success is 100% for all tested inputs indicating strong key dependence and a reliable operation. Additionally, the ciphertext shows that there is no skewed distribution of bytes and the text follows a uniform distribution, which verifies that there is a high randomness and a strong resistance against statistical attacks. Overall, the results confirm the validity of ChaCha20 as a fast, secure and reliable cryptographic solution that can be implemented in the modern software-based security applications such as real-time communications and high throughput data systems.

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Published

2026-09-04

How to Cite

Abdulsamad Ibrahim. (2026). Experimental Evaluation of the Performance and Security of the ChaCha20 Stream Cipher Using Python. International Journal of Computer Information Systems and Industrial Management Applications, 18(22s), 2213–2222. https://doi.org/10.70917/ijcisim-2026-5838

Issue

Section

Original Articles