IEEE/ACM Trans Comput Biol Bioinform. 2022 Jul-Aug;19(4):2385-2398. doi: 10.1109/TCBB.2021.3063388. Epub 2022 Aug 8.
With the rapid development of bioinformatics and the availability of genetic sequencing technologies, genomic data has been used to facilitate personalized medicine. Cloud computing, features as low cost, rich storage and rapid processing can precisely respond to the challenges brought by the emergence of massive genomic data. Considering the security of cloud platform and the privacy of genomic data, we first introduce P2GT which utilizes key-policy attribute-based encryption to realize genomic data access control with unbounded attributes, and employs equality test algorithm to achieve personalized medicine test by matching digitized single nucleotide polymorphisms (SNPs) directly on the users' ciphertext without encrypting multiple times. We then propose an enhanced scheme P2GT+, which adopts identity-based encryption with equality test supporting flexible joint authorization to realize privacy-preserving paternity test, genetic compatibility test and disease susceptibility test over the encrypted SNPs with P2GT. We prove the security of proposed schemes and conduct extensive experiments with the 1,000 Genomes dataset. The results show that P2GT and P2GT+ are practical and scalable enough to meet the privacy-preserving and authorized genetic testing requirements in cloud computing.
随着生物信息学的快速发展和基因测序技术的普及，基因组数据已被用于促进个性化医疗。云计算具有成本低、存储丰富和处理速度快等特点，可以精确应对大规模基因组数据出现带来的挑战。考虑到云平台的安全性和基因组数据的隐私性，我们首先介绍了 P2GT，它利用基于密钥策略的属性加密来实现具有无限属性的基因组数据访问控制，并采用等式测试算法通过直接在用户密文上匹配数字化单核苷酸多态性（SNP），而无需多次加密，从而实现个性化医疗测试。然后，我们提出了一个增强的方案 P2GT+，它采用支持灵活联合授权的基于身份的加密和等式测试，来实现对加密 SNP 进行隐私保护的亲子关系测试、遗传兼容性测试和疾病易感性测试。我们证明了所提出方案的安全性，并使用 1000 基因组数据集进行了广泛的实验。结果表明，P2GT 和 P2GT+ 具有足够的实用性和可扩展性，可以满足云计算中隐私保护和授权基因测试的要求。
