“Multi-layer” encryption of medical data in DNA for highly-secure storage

The exponential increasement and the attributes of medical data drive the requirement for secure medical data archiving. DNA data storage shows promise for storing sensitive and important data like medical records due to its high density and endurance. Nevertheless, current DNA data storage working scheme generally does not fully consider the data encryption, posing a risk of data corruption by routine DNA sequencing. Here, we designed a "multi-layer" encryption pipeline for medical data archiving. Initially, digital information was encrypted using Blowfish algorithm at information technology (IT) layer, followed by two-layer data encryption at the biotechnology (BT) layer. The first BT layer exploited the molecular weight of synthetic DNA or nucleoside to encrypt the key, while the second BT layer encrypted digital information within DNA sequences. Consequently, decryption involved layer-by-layer interpretation of data, including mass spectroscopy, sequencing, and Blowfish decryption, significantly enhancing data security. Utilizing mass spectroscopy to retrieve information allows for employment of both natural and unnatural nucleosides, as well as their synthetic oligonucleotides, for data storage, thereby considerably boosting scalability. Our work implies expanded flexibility of DNA-based data storage, highlighting the potential for leveraging various physical and chemical characteristics of DNA molecules to encode and access digital information.

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Institutions

Publication Details

Journal
Materials Today Bio
Published
2024-09-01
DOI
https://doi.org/10.1016/j.mtbio.2024.101221
Citations
10
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
2.34

Funders

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article

“Multi-layer” encryption of medical data in DNA for highly-secure storage

Yu Wang, Hui Mei, Xue Chen, Haibo Zhou et al.
10 citations
Materials Today Bio
DNA and Biological Computing
2.34
article

“Multi-layer” encryption of medical data in DNA for highly-secure storage

Yu Wang, Hui Mei, Xue Chen, Haibo Zhou, Shanze Chen, Lingwei Wang, Xiaoluo Huang, Jiaxin Xu
article en
10 citations

Abstract

The exponential increasement and the attributes of medical data drive the requirement for secure medical data archiving. DNA data storage shows promise for storing sensitive and important data like medical records due to its high density and endurance. Nevertheless, current DNA data storage working scheme generally does not fully consider the data encryption, posing a risk of data corruption by routine DNA sequencing. Here, we designed a "multi-layer" encryption pipeline for medical data archiving. Initially, digital information was encrypted using Blowfish algorithm at information technology (IT) layer, followed by two-layer data encryption at the biotechnology (BT) layer. The first BT layer exploited the molecular weight of synthetic DNA or nucleoside to encrypt the key, while the second BT layer encrypted digital information within DNA sequences. Consequently, decryption involved layer-by-layer interpretation of data, including mass spectroscopy, sequencing, and Blowfish decryption, significantly enhancing data security. Utilizing mass spectroscopy to retrieve information allows for employment of both natural and unnatural nucleosides, as well as their synthetic oligonucleotides, for data storage, thereby considerably boosting scalability. Our work implies expanded flexibility of DNA-based data storage, highlighting the potential for leveraging various physical and chemical characteristics of DNA molecules to encode and access digital information.

Materials Today BioVol. 28
BGI Group (China) (CN), Jinan University (CN), Southern University of Science and Technology (CN), Synthetic Genomics (United States) (US), Shenzhen Institutes of Advanced Technology (CN), Shenzhen Second People's Hospital (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 11%
DNA and Biological Computing
2.34
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