A Comprehensive Methodology for Data Compression and Decompression Utilizing Huffman Coding, LZW Compression, and Run-Length Encoding, Integrated with Data Encryption Standard (DES) and Advanced Encryption Standard (AES) for Enhanced Security
Sangeen Khan
Sangeen Khan, Department of Communication Engineering University of Science and Technology Beijing China.
Manuscript received on 20 February 2024 | Revised Manuscript received on 24 October 2024 | Manuscript Accepted on 15 November 2024 | Manuscript published on 30 November 2024 | PP: 7-13 | Volume-4 Issue-2, November 2024 | Retrieval Number: 100.1/ijcns.A142704010524 | DOI: 10.54105/ijcns.A1427.04021124
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© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With advancements in communication technologies, transitioning from 5G to 6G systems has led to exponential data growth, requiring secure and efficient data transmission solutions. This study integrates data compression techniques-Huffman Coding, Lempel-Ziv-Welch (LZW), and Run-Length Encoding (RLE)-with symmetric encryption algorithms, AES (Advanced Encryption Standard) and DES (Data Encryption Standard). The primary goal is to enhance computational performance while ensuring data security. Using a 32-byte dataset and implementing the algorithms in Go language via Visual Studio IDE, results demonstrate the significant reduction in encryption time when combining compression and encryption. Among the AES combinations, AES with Huffman Coding showed the highest efficiency, reducing encryption time by approximately 15% compared to standalone AES. Similarly, DES paired with LZW compression achieved a 20% improvement in computational time over standalone DES. The findings emphasize that selecting the optimal combination depends on data type and user requirements, facilitating secure and efficient communication in high-bandwidth, low-latency 6G systems. This research underscores the potential of cryptography, combined with compression, to enhance data transmission efficiency without compromising security. The integration approach highlights cryptographic strength in safeguarding big data, addressing challenges in modern technologies like the Internet of Everything (IoE). These results establish a foundation for future secure communication frameworks, promoting reliable and scalable cryptographic solutions tailored for 6G and beyond.
Keywords: 6G, AES, Go Language, Computational Performance, Big data.
Scope of the Article: Cryptographic Algorithms