Privacy-Preserving Whole Genome Sequence Processing through Proxy-Aided ORAM

Karvelas, Nikolaos P.; Andreas, Peter; Katzenbeisser, Stefan; Tews, Erik; Hamacher, Kay

doi:10.1145/2665943.2665962

Cited by 27 publications

(17 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ayday et al proposed a scheme to protect the privacy of users' genomic data yet enable medical units to access the genomic data in order to conduct medical tests or to develop personalized medicine methods [2]. Karvelas et al proposed using the oblivious RAM mechanisms to access genomic data (that is stored at a third party) and secure twoparty computation protocols to compute various functionalities on the data [3]. Recently, Wang et al proposed private edit distance protocols to find similar patients (e.g., across several hospitals) [4].…”

Section: Related Workmentioning

confidence: 99%

Cryptographic Solutions for Credibility and Liability Issues of Genomic Data

Ayday¹,

Tang²,

Yılmaz³

2019

IEEE Trans. Dependable and Secure Comput.

View full text Add to dashboard Cite

Abstract-In this work, we consider a scenario that includes an individual sharing his genomic data (or results obtained from his genomic data) with a service provider. In this scenario, (i) the service provider wants to make sure that received genomic data (or results) in fact belongs to the corresponding individual (and computed correctly), (ii) the individual wants to provide a digital consent along with his data specifying whether the service provider is allowed to further share his data, and (iii) if his data is shared without his consent, the individual wants to determine the service provider that is responsible for this leakage. We propose two schemes based on homomorphic signature and aggregate signature that links the information about the legitimacy of the data to the consent and the phenotype of the individual. Thus, to verify the data, each party also needs to use the correct consent and phenotype of the individual who owns the data.

show abstract

Section: Related Workmentioning

confidence: 99%

Cryptographic Solutions for Credibility and Liability Issues of Genomic Data

Ayday¹,

Tang²,

Yılmaz³

2019

IEEE Trans. Dependable and Secure Comput.

View full text Add to dashboard Cite

show abstract

“…They also implemented a prototype system in an Android App. In [Karvelas et al, 2014], authors propose a technique to store genomic data in encrypted form, use an Oblivious RAM to access the desired data without leaking the access pattern, and finally run secure two-party computation protocol to privately compute the required function on the retrieved encrypted genomic data. The proposed construction includes two separate servers: cloud and proxy.…”

Section: Viia Healthcarementioning

confidence: 99%

Privacy in the Genomic Era

et al. 2015

View full text Add to dashboard Cite

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with traits and certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward.

show abstract

“…These advances on protocol efficiency have motivated the apparition of new applications such as, biometric identification [39]. Typically, ORAMs are designed and used to solve the problem of DB outsourcing [40]. This model would require the user to execute various ORAM primitives so that the remote database is correctly shuffled.…”

Section: Protocol Extensionsmentioning

confidence: 99%

Efficient Verifiable Computation of XOR for Biometric Authentication

Abidin

Aly

Rúa

et al. 2016

Cryptology and Network Security

View full text Add to dashboard Cite

Abstract. This work addresses the security and privacy issues in remote biometric authentication by proposing an efficient mechanism to verify the correctness of the outsourced computation in such protocols. In particular, we propose an efficient verifiable computation of XORing encrypted messages using an XOR linear message authentication code (MAC) and we employ the proposed scheme to build a biometric authentication protocol. The proposed authentication protocol is both secure and privacy-preserving against malicious (as opposed to honestbut-curious) adversaries. Specifically, the use of the verifiable computation scheme together with an homomorphic encryption protects the privacy of biometric templates against malicious adversaries. Furthermore, in order to achieve unlinkability of authentication attempts, while keeping a low communication overhead, we show how to apply Oblivious RAM and biohashing to our protocol. We also provide a proof of security for the proposed solution. Our simulation results show that the proposed authentication protocol is efficient.

show abstract

Privacy-Preserving Whole Genome Sequence Processing through Proxy-Aided ORAM

Cited by 27 publications

References 31 publications

Cryptographic Solutions for Credibility and Liability Issues of Genomic Data

Cryptographic Solutions for Credibility and Liability Issues of Genomic Data

Privacy in the Genomic Era

Efficient Verifiable Computation of XOR for Biometric Authentication

Contact Info

Product

Resources

About