Functional genomics data: privacy risk assessment and technological mitigation
The generation of functional genomics data by next-generation sequencing has increased
greatly in the past decade. Broad sharing of these data is essential for research …
greatly in the past decade. Broad sharing of these data is essential for research …
Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility
A Brauneck, L Schmalhorst, S Weiss, L Baumbach… - Genome Biology, 2024 - Springer
Genomic data holds huge potential for medical progress but requires strict safety measures
due to its sensitive nature to comply with data protection laws. This conflict is especially …
due to its sensitive nature to comply with data protection laws. This conflict is especially …
SoK: Fully homomorphic encryption compilers
Fully Homomorphic Encryption (FHE) allows a third party to perform arbitrary computations
on encrypted data, learning neither the inputs nor the computation results. Hence, it provides …
on encrypted data, learning neither the inputs nor the computation results. Hence, it provides …
Efficient bootstrap** for approximate homomorphic encryption with non-sparse keys
We present a bootstrap** procedure for the full-RNS variant of the approximate
homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17, SAC 18). Compared …
homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17, SAC 18). Compared …
The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition
Concerns regarding inappropriate leakage of sensitive personal information as well as
unauthorized data use are increasing with the growth of genomic data repositories …
unauthorized data use are increasing with the growth of genomic data repositories …
Memfhe: End-to-end computing with fully homomorphic encryption in memory
The increasing amount of data and the growing complexity of problems have resulted in an
ever-growing reliance on cloud computing. However, many applications, most notably in …
ever-growing reliance on cloud computing. However, many applications, most notably in …
Secure tumor classification by shallow neural network using homomorphic encryption
Background Disclosure of patients' genetic information in the process of applying machine
learning techniques for tumor classification hinders the privacy of personal information …
learning techniques for tumor classification hinders the privacy of personal information …
Privacy-enhancing technologies in biomedical data science
The rapidly growing scale and variety of biomedical data repositories raise important privacy
concerns. Conventional frameworks for collecting and sharing human subject data offer …
concerns. Conventional frameworks for collecting and sharing human subject data offer …
Sine series approximation of the mod function for bootstrap** of approximate HE
CS Jutla, N Manohar - Annual International Conference on the Theory and …, 2022 - Springer
While it is well known that the sawtooth function has a point-wise convergent Fourier series,
the rate of convergence is not the best possible for the application of approximating the mod …
the rate of convergence is not the best possible for the application of approximating the mod …
TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation
M Yang, C Zhang, X Wang, X Liu, S Li, J Huang… - Cell Systems, 2022 - cell.com
The statistical power of genome-wide association studies (GWASs) is affected by the
effective sample size. However, the privacy and security concerns associated with individual …
effective sample size. However, the privacy and security concerns associated with individual …