Abstract
With the rapid development of genomic sequencing technology, the cost of obtaining personal genomic data and analyzing it effectively has been gradually reduced. The analysis and utilization of genomic data have gradually come into the public view, the privacy leakage of genomic data has aroused the attention of researchers. Genomic data has unique format and a large amount of data, but the existing genetic privacy protection schemes often fail to consider security, availability and efficiency together. In this paper, we analyzed widely used genomic data file formats and designed a hybrid encryption scheme for large genomic data files. Firstly, we designed a key agreement protocol based on RSA asymmetric cryptography. Secondly, we used AES symmetric encryption to encrypt the genomic data by optimizing the packet processing of files and multithreading encryption, and improved the usability by assisting the computing platform with key management. Software implementation indicates that the scheme can be applied to the secure transmission of genomic data in the network environment and provide an efficient encryption method for the privacy protection of genomic data.
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Notes
- 1.
Here K is the AES encryption key, \( K_{p} \) is the public key of RSA, \( K_{s} \) is the private key of RSA, m is the plaintext, \( H(\bullet ) \) represents the hash value.
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Acknowledgment
This project is supported by the National Key Research and Development Program of China (No. 2016YFC1000307), the National Natural Science Foundation of China (No. 61571024, No. 61971021) and Aeronautical Science Foundation of China (No. 2018ZC51016) for valuable helps.
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Jiang, Y., Shang, T., Liu, J., Cao, Z., Geng, Y. (2019). An Efficient Hybrid Encryption Scheme for Large Genomic Data Files. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1137. Springer, Singapore. https://doi.org/10.1007/978-981-15-1922-2_15
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DOI: https://doi.org/10.1007/978-981-15-1922-2_15
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