Achieving Scalable and Privacy-Preserving Whole Genome Variant Queries
Event details
| Date | 27.08.2018 |
| Hour | 10:15 |
| Speaker | Dr. Mete Akgün, University of Tübingen, Germany |
| Location | |
| Category | Conferences - Seminars |
Abstract
Diagnosis and treatment methods based on big genomic data are becoming widespread as the cost of genome sequencing decreases gradually. In this context, disease-gene association studies are of great importance. The genomic data is very sensitive when compared to other data types and contains information about the individual and his / her relatives. Many studies have shown that this information can be obtained from the query-response pairs on genomic databases. In this talk, I will explain a method that uses secure multi-party computation (SMPC) to query genomic databases in a privacy-protected manner. Our solution allows genomic databases to be safely stored in semi-honest cloud environments. It provides data privacy, query privacy, and output privacy. It allows multiple genomic databases to be queried at the same time. Unlike the previous studies, it is possible to query multiple databases at reasonable times. We measure the performance of our solution with parameters that are close to the medical systems in the real world. It is possible to query a genomic database with 3000000 variants with 5 genomic variant conditions under 120 ms. It is possible to query 10000 genomic databases, each with 3 million variants, with 5 genomic variant conditions under 1 second. These running times are very convincing in terms of integration into real medical systems. To the best of our knowledge, this is the first solution that provides this performance for querying multiple genomic datasets.
Biography
Dr. Mete Akgün is a postdoctoral researcher at the University of Tübingen. He received his M.S. and Ph.D. degrees from Department of Computer Science, Boğaziçi University, İstanbul, Turkey, in 2009 and 2016, respectively under the supervision of Prof. Mehmet Ufuk Çağlayan. Meteʼs research interests include privacy-enhancing technologies (including big data and genomic privacy), security protocols and bioinformatics.
Diagnosis and treatment methods based on big genomic data are becoming widespread as the cost of genome sequencing decreases gradually. In this context, disease-gene association studies are of great importance. The genomic data is very sensitive when compared to other data types and contains information about the individual and his / her relatives. Many studies have shown that this information can be obtained from the query-response pairs on genomic databases. In this talk, I will explain a method that uses secure multi-party computation (SMPC) to query genomic databases in a privacy-protected manner. Our solution allows genomic databases to be safely stored in semi-honest cloud environments. It provides data privacy, query privacy, and output privacy. It allows multiple genomic databases to be queried at the same time. Unlike the previous studies, it is possible to query multiple databases at reasonable times. We measure the performance of our solution with parameters that are close to the medical systems in the real world. It is possible to query a genomic database with 3000000 variants with 5 genomic variant conditions under 120 ms. It is possible to query 10000 genomic databases, each with 3 million variants, with 5 genomic variant conditions under 1 second. These running times are very convincing in terms of integration into real medical systems. To the best of our knowledge, this is the first solution that provides this performance for querying multiple genomic datasets.
Biography
Dr. Mete Akgün is a postdoctoral researcher at the University of Tübingen. He received his M.S. and Ph.D. degrees from Department of Computer Science, Boğaziçi University, İstanbul, Turkey, in 2009 and 2016, respectively under the supervision of Prof. Mehmet Ufuk Çağlayan. Meteʼs research interests include privacy-enhancing technologies (including big data and genomic privacy), security protocols and bioinformatics.
Practical information
- General public
- Free
- This event is internal
Organizer
- Professor Bryan Ford
Contact
- Dr. Philipp Jovanovic