Analysis of Encryption and Lossless Compression Techniques for Secure Data Transmission

Singh, Sadhna; Devgon, Raaghavv

doi:10.1109/ccoms.2019.8821637

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…Ultimately, this taxonomy improves the clarity and accessibility of data reduction techniques, facilitating their evaluation and selection for specific data management and analysis purposes. In the proposed taxonomy, data reduction approaches are divided into two main categories:  Lossless data reduction techniques [14,21,22]: these focus on identifying redundancies, patterns, and other inherent characteristics within the data to eliminate or minimize unnecessary and repetitive information. Reducing the data size without any loss is remarkable.…”

Section: Proposed Taxonomymentioning

confidence: 99%

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Analyzing Data Reduction Techniques: An Experimental Perspective

Fernandes,

Carvalho,

Pereira

et al. 2024

Applied Sciences

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The exponential growth in data generation has become a ubiquitous phenomenon in today’s rapidly growing digital technology. Technological advances and the number of connected devices are the main drivers of this expansion. However, the exponential growth of data presents challenges across different architectures, particularly in terms of inefficient energy consumption, suboptimal bandwidth utilization, and the rapid increase in data stored in cloud environments. Therefore, data reduction techniques are crucial to reduce the amount of data transferred and stored. This paper provides a comprehensive review of various data reduction techniques and introduces a taxonomy to classify these methods based on the type of data loss. The experiments conducted in this study include distinct data types, assessing the performance and applicability of these techniques across different datasets.

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Section: Proposed Taxonomymentioning

confidence: 99%

“…Lossless data reduction techniques [14,21,22]: these focus on identifying redundancies, patterns, and other inherent characteristics within the data to eliminate or minimize unnecessary and repetitive information. Reducing the data size without any loss is remarkable.…”

mentioning

confidence: 99%

Analyzing Data Reduction Techniques: An Experimental Perspective

Fernandes,

Carvalho,

Pereira

et al. 2024

Applied Sciences

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“…Figure 2: Run-length encoding for two symbols (Souley et. al, 2014) In this algorithm, repeated pixel can be substituted by a number that indicate which pixel value is repeated and how many times it is repeated (Singh and Devgon, 2019). The occurrence of 0 and 1 in sequence counts.…”

Section: Run Length Encoding (Rle)mentioning

confidence: 99%

Evaluation of Lossless Algorithms for Data Compression

Sharma¹,

Batra²

2020

Ethics and Information Technology

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“…Compression ratio (CR) [32] is the ratio of the size of the file post compression, compared to the original file and is mathematically expressed in eq (21). CR is used to determine the efficiency of the compression, higher the CR better the compression [18].…”

Section: Compression Ratiomentioning

confidence: 99%

Performance analysis of compression algorithms for information security: A Review

Sharma

Batra

2018

ICST Transactions on Scalable Information Systems

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Data compression is a vital part of information security, since compressed data is much more secure and convenient to handle. Effective data compression technique creates an effective, secure, easy communicable & redundant data. There are two types of compression algorithmic techniques:-lossy and lossless. These techniques can be applied to any data format like text, audio, video or image file. The primary objective of this study was to analyse data compression techniques used for information security techniques like steganography, cryptography etc. Four each, lossy and lossless techniques are implemented and evaluated on parameters like-file size, saving percentage, time, compression ratio and speed. Detailed analysis shows that the lossy techniques performs better quantitatively whereas lossless is better qualitatively. However, lossless techniques are more effective as there is no data loss during the process. Among all, Huffman encoding outperforms other algorithms.

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Analysis of Encryption and Lossless Compression Techniques for Secure Data Transmission

Cited by 7 publications

References 12 publications

Analyzing Data Reduction Techniques: An Experimental Perspective

Analyzing Data Reduction Techniques: An Experimental Perspective

Evaluation of Lossless Algorithms for Data Compression

Performance analysis of compression algorithms for information security: A Review

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