Privacy-Preserving and Robust Watermarking on Sequential Genome Data using Belief Propagation and Local Differential Privacy-猫眼课题宝

DOI：

10.1101/2020.09.04.283135

发表时间：

2020-09

期刊：

bioRxiv

影响因子：

通讯作者：

中科院分区：

其他

文献类型：

作者：

Abdullah Çaglar Öksüz;Erman Ayday;U. Güdükbay

自1990年人类基因组计划开始以来，基因组数据一直是生物学和计算机科学的研究主题。从那时起，用于医疗和社会目的的基因组测序变得越来越容易获得和负担得起。基因组数据可以在公共网站上共享，也可以与服务提供商共享。然而，即使在部分共享条件下，这种共享也会损害捐赠者的隐私。我们主要关注未经授权共享这些基因组数据所带来的责任方面。数字水印技术是解决数据共享中的责任问题的技术之一。结果为了检测恶意通信者和服务提供者（SP）--其目的是在未经个人同意的情况下共享基因组数据而不被发现--提出了一种基于置信传播算法的序列基因组数据水印方法。在我们的方法中，我们有两个标准要满足。(i)嵌入鲁棒的水印，使恶意的对手不能通过修改篡改水印，并以高概率识别（ii）实现所有数据共享与SP的双本地差分隐私。为了保护系统对单SP和共谋攻击的鲁棒性，我们考虑公开可用的基因组信息，如次要等位基因频率，连锁不平衡，表型信息和家族信息。我们提出的方案实现了100%的检测率对单SP攻击只有3%的水印长度。对于共谋攻击的最坏情况（50%的SP是恶意的），使用5%的水印长度实现80%的检测，使用10%的水印长度实现90%的检测。在所有情况下，加密对精确度的影响仍然可以忽略不计，并确保高度隐私。https://github.com/acoksuz/PPRW_SGD_BPLDP联系方式abdullahcaglaroksuz@gmail.com

Motivation 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. 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, ϵ’s impact on precision remained negligible and high privacy is ensured. Availability https://github.com/acoksuz/PPRW_SGD_BPLDP Contact abdullahcaglaroksuz@gmail.com

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

文献摘要

相似文献