GenInfoGuard—A Robust and Distortion-Free Watermarking Technique for Genetic Data

Iftikhar, Sadaf; Khan, Sharifullah; Anwar, Zahid; Kamran, Muhammad

doi:10.1371/journal.pone.0117717

Cited by 4 publications

(5 citation statements)

References 26 publications

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“…Kozat et al [60] proposed a steganographybased watermarking scheme for sequential electrocardiography data to hide private meta-data like the patient's social security number or birth date for data ownership authentication. Iftikhar et al [61] proposed a robust and distortion-free watermarking scheme called GenInfoGuard for genomic data. Iftikhar's scheme uses features selected from the data for embedding a watermark on.…”

Section: Watermarking Genomic Datamentioning

confidence: 99%

Privacy-preserving and robust watermarking on sequential genome data using belief propagation and local differential privacy

2021

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Motivation Genome data is a subject of study for both biology and computer science since the start of the Human Genome Project in 1990. Since then, genome sequencing for medical and social purposes becomes more and more available and affordable. Genome data can be shared on public websites or with service providers. However, this sharing compromises the privacy of donors even under partial sharing conditions. We mainly focus on the liability aspect ensued by the unauthorized sharing of these genome data. One of the techniques to address the liability issues in data sharing is the watermarking mechanism. Results To detect malicious correspondents and service providers (SPs) -whose aim is to share genome data without individuals’ consent and undetected-, we propose a novel watermarking method on sequential genome data using belief propagation algorithm. In our method, we have two criteria to satisfy. (i) Embedding robust watermarks so that the malicious adversaries can not temper the watermark by modification and are identified with high probability (ii) Achieving ε-local differential privacy in all data sharings with SPs. For the preservation of system robustness against single SP and collusion attacks, we consider publicly available genomic information like Minor Allele Frequency, Linkage Disequilibrium, Phenotype Information and Familial Information. Our proposed scheme achieves 100% detection rate against the single SP attacks with only 3% watermark length. For the worst case scenario of collusion attacks (50% of SPs are malicious), 80% detection is achieved with 5% watermark length and 90% detection is achieved with 10% watermark length. For all cases, the impact of ε on precision remained negligible and high privacy is ensured. Availability https://github.com/acoksuz/PPRW_SGD_BPLDP Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Watermarking Genomic Datamentioning

confidence: 99%

Privacy-preserving and robust watermarking on sequential genome data using belief propagation and local differential privacy

2021

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“…Kozat et al (2008) proposed a steganography-based watermarking scheme for sequential electrocardiography data to hide private meta-data. Iftikhar et al (2015) proposed a robust and distortionfree watermarking scheme, GenInfoGuard, for genomic data. They use features selected from the data for watermark embedding.…”

Section: Related Workmentioning

confidence: 99%

Privacy-Preserving and Robust Watermarking on Sequential Genome Data using Belief Propagation and Local Differential Privacy

Oksuz

Ayday

Güdükbay

2020

Preprint

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Genome data is a subject of study for both biology and computer science since the start of Human Genome Project in 1990. Since then, genome sequencing for medical and social purposes becomes more and more available and affordable. Genome data can be shared on public websites or with service providers. However, this sharing compromises the privacy of donors even under partial sharing conditions. We mainly focus on the liability aspect ensued by unauthorized sharing of these genome data. One of the techniques to address the liability issues in data sharing is watermarking mechanism. To detect malicious correspondents and service providers (SPs) -whose aim is to share genome data without individuals' consent and undetected-, we propose a novel watermarking method on sequential genome data using belief propagation algorithm. In our method, we have two criteria to satisfy. (i) Embedding robust watermarks so that the malicious adversaries can not temper the watermark by modification and are identified with high probability (ii) Achieving ε-local differential privacy in all data sharings with SPs. For the preservation of system robustness against single SP and collusion attacks, we consider publicly available genomic information like Minor Allele Frequency, Linkage Disequilibrium, Phenotype Information and Familial Information. Our proposed scheme achieves 100% detection rate against the single SP attacks with only 3% watermark length. For the worst case scenario of collusion attacks (50% of SPs are malicious), 80% detection is achieved with 5% watermark length and 90% detection is achieved with 10% watermark length. For all cases, ε's impact on precision remained negligible and high privacy is ensured.

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“…In fact, genetic data watermarking is a promising technique for integrity, traceability or ownership protection. Concretely, we have added the watermarking scheme in (Iftikhar et al, 2015) that supports ownership and integrity protection properties for digital genetic data. In the following, we present operators for watermarking and the detection of watermarks that can be composed with the ones for encryption and fragmentation.…”

Section: The Coshed Approachmentioning

confidence: 99%

“…Watermarks are represented as a type WATERMARK whose first argument represents the watermarking scheme (for now we have implemented only one scheme GIG (Iftikhar et al, 2015) Figure 6: Watermarking operators see Fig. 6, respectively for watermark application (as part of the privacy-enhancing technologies of ADT Privy) and watermark detection as used in queries (ADT Query).…”

Section: The Coshed Approachmentioning

confidence: 99%

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Constructive Privacy for Shared Genetic Data

Boujdad

Südholt

2018

Proceedings of the 8th International Conference on Cloud Computing and Services Science

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Abstract:The need for the sharing of genetic data, for instance, in genome-wide association studies is incessantly growing. In parallel, serious privacy concerns rise from a multi-party access to genetic information. Several techniques, such as encryption, have been proposed as solutions for the privacy-preserving sharing of genomes. However, existing programming means do not support guarantees for privacy properties and the performance optimization of genetic applications involving shared data. We propose two contributions in this context. First, we present new cloud-based architectures for cloud-based genetic applications that are motivated by the needs of geneticians. Second, we propose a model and implementation for the composition of watermarking with encryption, fragmentation, and client-side computations for the secure and privacy-preserving sharing of genetic data in the cloud.

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GenInfoGuard—A Robust and Distortion-Free Watermarking Technique for Genetic Data

Cited by 4 publications

References 26 publications

Privacy-preserving and robust watermarking on sequential genome data using belief propagation and local differential privacy

Privacy-preserving and robust watermarking on sequential genome data using belief propagation and local differential privacy

Privacy-Preserving and Robust Watermarking on Sequential Genome Data using Belief Propagation and Local Differential Privacy

Constructive Privacy for Shared Genetic Data

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