Enhancing Secured QR Code Large Storage Capacity Through Steganography and Compression Techniques

QR codes are widely used for quick and efficient data transmission in various applications. However, their storage capacity is limited and not secured, which can be difficult to save large dataset and expose to the data leakage. To address this issue, researchers have explored various methods to extend the storage capacity without altering the QR code structure and have secured information inside. This research is to enhance the storage capacity of QR codes by combining steganography and compression techniques. Steganography allows for the concealment of additional data inside the QR code’s visual elements, while compression reduces the size of the data being encoded. In this study, we implement a two-step approach: first, data is embedded using steganographic techniques then it is compressed using advanced algorithms to minimize its size. By applying these methods, the overall storage efficiency is significantly increased without compromising the code’s scan ability. The principal results of the research demonstrate that the combined use of steganography and compression can increase QR code storage capacity by up to 20% and it is secured. Major conclusions indicate that this method can effectively extend the QR code applications in industries requiring the encoding of large datasets, such as banking and authorization function. This study presents a novel approach to overcoming QR code storage limitations, offering a practical solution for maximizing data storage and totally secured.

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Publication Details

Journal
International Journal of Advanced Research in Computational Thinking and Data Science
Published
2025-03-05
DOI
https://doi.org/10.37934/ctds.5.1.2849
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Secured QR Code Large Storage Capacity Through Steganography and Compression Techniques

Azizi Abas, Fazli Azzali, Roshidi Din
International Journal of Advanced Research in Computational Thinking and Data Science
Caching and Content Delivery
article

Enhancing Secured QR Code Large Storage Capacity Through Steganography and Compression Techniques

Azizi Abas, Fazli Azzali, Roshidi Din
article en

Abstract

QR codes are widely used for quick and efficient data transmission in various applications. However, their storage capacity is limited and not secured, which can be difficult to save large dataset and expose to the data leakage. To address this issue, researchers have explored various methods to extend the storage capacity without altering the QR code structure and have secured information inside. This research is to enhance the storage capacity of QR codes by combining steganography and compression techniques. Steganography allows for the concealment of additional data inside the QR code’s visual elements, while compression reduces the size of the data being encoded. In this study, we implement a two-step approach: first, data is embedded using steganographic techniques then it is compressed using advanced algorithms to minimize its size. By applying these methods, the overall storage efficiency is significantly increased without compromising the code’s scan ability. The principal results of the research demonstrate that the combined use of steganography and compression can increase QR code storage capacity by up to 20% and it is secured. Major conclusions indicate that this method can effectively extend the QR code applications in industries requiring the encoding of large datasets, such as banking and authorization function. This study presents a novel approach to overcoming QR code storage limitations, offering a practical solution for maximizing data storage and totally secured.

International Journal of Advanced Research in Computational Thinking and Data ScienceVol. 5(1)
Northern University of Malaysia (MY)
Openalex Percentile: Top 96%
Caching and Content Delivery
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