Arcitech: Journal of Computer Science and Artificial Intelligence
Vol. 5 No. 1 (2025): June 2025

Analisis Komparatif Performa AES-GCM dan ChaCha20-Poly1305 dalam Enkripsi Dokumen PDF Berbasis AEAD

Patria, Muhammad (Unknown)
Andriati, Dea Andini (Unknown)



Article Info

Publish Date
30 Jun 2025

Abstract

Digital transformation in electronic document services demands encryption mechanisms that are not only cryptographically secure but also performance-efficient. While AES-GCM and ChaCha20-Poly1305 are widely adopted AEAD algorithms, prior research has largely focused on their use in communication protocols or IoT devices, rather than in encrypting PDF documents. This study addresses that gap by empirically comparing both algorithms in real-world digital document processing scenarios. A quantitative experimental method was applied across two scenarios: mass processing of 5,000 small-to-medium PDF files (100KB–8MB), and individual processing of large files (1MB–200MB). Five performance metrics were analyzed: encryption time, decryption time, total processing time, stability, and throughput. Results show that AES-GCM consistently outperformed ChaCha20-Poly1305 across all metrics, offering faster processing and greater stability. Both algorithms produced a constant file size overhead of 28 bytes, which was negligible in terms of storage efficiency. This study contributes to the literature by providing empirical evidence to guide the selection of encryption algorithms in high-performance digital document storage systems.

Copyrights © 2025






Journal Info

Abbrev

arcitech

Publisher

Subject

Computer Science & IT

Description

Arcitech: Journal of Computer Science and Artificial Intelligence, is an Open Access and peer-reviewed journal published by the State Islamic Institute (IAIN) Curup. This journal focuses on the field of computer science and artificial intelligence covering all aspects of information technology, ...