Abstract
This paper proposes the first robust watermarking method of outsourced or shared genomic data in the context of genome-wide association studies (GWAS) with the primary purpose of identifying the individual or entity at the origin of an illegal information redistribution or disclosure. Our scheme’s first unique feature is that it employs a database watermarking strategy to take advantage of the fact that GWAS data are stored in variant call format (VCF) files, which have a database-like structure. Second, it proposes a quantization index modulation based on watermarking modulation for GWAS data under the constraint of not interfering with identifying candidate variants or genes involved in the pathology. We evaluate the theoretical performance of our method in terms of watermarking insertion capacity, distortion, and robustness against different attacks. Experimental results conducted on real data and the weighted-sum statistic (WSS) GWAS study demonstrate the efficiency of the proposed scheme and that it can be used for identifying the cloud service providers (geneticists) at the origin of an information disclosure even if the genotype data has been modified.
R. Bellafqira and M. Al-Ghadi—Equal contributions.
This work was supported in part by the French Government support granted to the Labex CominLabs and managed by the ANR through the “Investing for the Future” Program under Grant ANR-10-LABX-07-01 through the project TADOP.
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Bellafqira, R., Al-Ghadi, M., Genin, E., Coatrieux, G. (2023). Robust and Imperceptible Watermarking Scheme for GWAS Data Traceability. In: Zhao, X., Tang, Z., Comesaña-Alfaro, P., Piva, A. (eds) Digital Forensics and Watermarking. IWDW 2022. Lecture Notes in Computer Science, vol 13825. Springer, Cham. https://doi.org/10.1007/978-3-031-25115-3_10
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