Privacy-preserving techniques of genomic data—a survey

Abstract

Genomic data hold salient information about the characteristics of a living organism. Throughout the past decade, pinnacle developments have given us more accurate and inexpensive methods to retrieve genome sequences of humans. However, with the advancement of genomic research, there is a growing privacy concern regarding the collection, storage and analysis of such sensitive human data. Recent results show that given some background information, it is possible for an adversary to reidentify an individual from a specific genomic data set. This can reveal the current association or future susceptibility of some diseases for that individual (and sometimes the kinship between individuals) resulting in a privacy violation. Regardless of these risks, our genomic data hold much importance in analyzing the well-being of us and the future generation. Thus, in this article, we discuss the different privacy and security-related problems revolving around human genomic data. In addition, we will explore some of the cardinal cryptographic concepts, which can bring efficacy in secure and private genomic data computation. This article will relate the gaps between these two research areas-Cryptography and Genomics.

iDASH secure genome analysis competition 2018: blockchain genomic data access logging, homomorphic encryption on GWAS, and DNA segment searching

“…Genome privacy is a twenty-first century challenge that has received relatively low publicity relative to risk, especially when compared to privacy issues surrounding social media or electronic health records [1][2][3]. This low profile is misleading because (1) the consequences of privacy breaches can be as ominous as those of other data types, and more extensive, since they can affect blood relatives; and (2) the ability for a motivated individual, a particular group, or a nation's government to conduct an effective attack has increased sharply in the past few years due to improvements in technology.…”

Privately computing set-maximal matches in genomic data

“…We observe that B (0) indicates whether a match has length greater than or equal to one. Using B (0) , we compute whether a match has length greater than or equal to two by setting B (1) j,i ← B (0) j,i ∧ B (0) j,i−1 . More generally, if B (k) indicates whether a match has length more than 2 k or not, then it can be updated to indicate if the length of a match is more than 2 k+1 by setting B…”

“…Fortunately, there is a variety of cryptographic techniques that allow us to create useful yet privacy-preserving systems for computation in genomic data (see [1] for a summary of various techniques). Even though theoretically it is possible to perform every computation in a private way, the generic techniques do not *Correspondence: katesot@mit.edu 1 MIT, CSAIL, 32 Vassar street, 02139 Cambridge, MA, USA Full list of author information is available at the end of the article necessarily preserve the efficiency and the accuracy of the original algorithm. Thus, constructing practical privacypreserving protocols has become a very active area of research.…”

“…Simultaneously, the extremely sensitive nature of this data imposes strict restrictions on its use. Fortunately, there is a variety of cryptographic techniques that allow us to create useful yet privacy-preserving systems for computation in genomic data (see [ 1 ] for a summary of various techniques). Even though theoretically it is possible to perform every computation in a private way, the generic techniques do not necessarily preserve the efficiency and the accuracy of the original algorithm.…”

SAFETY: Secure gwAs in Federated Environment through a hYbrid Solution

“…Because sharing genomic data in plaintext possesses serious privacy implications for the participants [11], [12], in addition to the approval from an institutional review board (IRB), collaborative research on shared genomic data often needs to satisfy two criteria at the same time — a) authorizing access to genomic data for research and b) preserving participants’ privacy and protecting the confidentiality of their genomic information [13]. That is why strict policies regarding genomic data sharing have been enforced, and generally, these policies are different in different regions of the world.…”