A Comprehensive Methodology for Data Compression and Decompression Utilizing Huffman Coding, LZW Compression, and RunLength Encoding, Integrated with Data Encryption Standard (DES) and Advanced Encryption Standard (AES) for Enhanced Security
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 Percent compared to standalone AES. Similarly, DES paired with LZW compression achieved a 20 Percent 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.
Authors
- Sangeen Khan (ORCID: https://orcid.org/0000-0003-4193-9340)
Publication Details
- Journal
- Indian Journal of Cryptography and Network Security
- Published
- 2024-11-28
- DOI
- https://doi.org/10.54105/ijcns.a1427.04021124
- Primary Topic
- Algorithms and Data Compression
- Type
- article
- Field-Weighted Citation Impact
- 0.00