Reference : A High-Throughput Method to Detect Privacy-Sensitive Human Genomic Data
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/22618
A High-Throughput Method to Detect Privacy-Sensitive Human Genomic Data
English
Cogo, Vinicius Vielmo mailto [Universidade de Lisboa - LaSIGE/FCUL]
Bessani, Alysson mailto [Universidade de Lisboa - LaSIGE/FCUL]
Couto, Francisco M. mailto [Universidade de Lisboa - LaSIGE/FCUL]
Verissimo, Paulo mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
12-Oct-2015
Proceedings of the 14th ACM Workshop on Privacy in the Electronic Society
101-110
Yes
International
[en] Finding the balance between privacy protection and data sharing is one of the main challenges in managing human genomic data nowadays. Novel privacy-enhancing technologies are required to address the known disclosure threats to personal sensitive genomic data without precluding data sharing. In this paper, we propose a method that systematically detects privacy-sensitive DNA segments coming directly from an input stream, using as reference a knowledge database of known privacy-sensitive nucleic and amino acid sequences. We show that adding our detection method to standard security techniques provides a robust, efficient privacy-preserving solution that neutralizes threats related to recently published attacks on genome privacy based on short tandem repeats, disease-related genes, and genomic variations. Current global knowledge on human genomes demonstrates the feasibility of our approach to obtain a comprehensive database immediately, which can also evolve automatically to address future attacks as new privacy-sensitive sequences are identified. Additionally, we validate that the detection method can be fitted inline with the NGS---Next Generation Sequencing---production cycle by using Bloom filters and scaling out to faster sequencing machines.
Interdisciplinary Centre for Security, Reliability and Trust
European Commission - EC ; Fundação para a Ciência e a Tecnologia
http://hdl.handle.net/10993/22618
10.1145/2808138.2808139
FnR ; FNR8149128 > Paulo Esteves Verissimo > IISD > Strategic RTnD Program on Information Infrastructure Security and Dependability > 01/01/2015 > 31/12/2019 > 2014

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
A High-Throughput Method to Detect Privacy Sensitive Human Denomic Data.pdfAuthor postprint375.58 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.