GenoPri
Quantifying and Protecting the Privacy of Genomic Data
Total Cost €
0EC-Contrib. €
0Partnership
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0GenoPri project word cloud
Explore the words cloud of the GenoPri project. It provides you a very rough idea of what is the project "GenoPri" about.
Project "GenoPri" data sheet
The following table provides information about the project.
| Coordinator |
BILKENT UNIVERSITESI VAKIF
Organization address contact info |
| Coordinator Country | Turkey [TR] |
| Project website | http://www.cs.bilkent.edu.tr/ |
| Total cost | 157˙845 € |
| EC max contribution | 157˙845 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2015 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2016 |
| Duration (year-month-day) | from 2016-05-01 to 2018-07-28 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | BILKENT UNIVERSITESI VAKIF | TR (BILKENT ANKARA) | coordinator | 157˙845.00 |
Map
Project objective
Genomic data carries a lot of sensitive information about its owner such as his predispositions to sensitive diseases, ancestors, physical attributes, and genomic data of his relatives (leading to interdependent privacy risks). Individuals share vast amount of information on the Web, and some of this information can be used to infer their genomic data. Hence, there is a need to clearly understand the privacy risks on genomic data of individuals considering publicly available information on the Web. It is also crucial to protect genomic privacy of individuals without compromising the utilization of genomic data in research and healthcare.
The two main objectives of this project are (i) to develop a new unifying framework for quantification of genomic privacy of individuals and (ii) to establish a complete framework for privacy-preserving utilization, sharing, and verification of genomic data under real-life threat models. Graph-based, iterative algorithms previously developed by the applicant to efficiently analyze big data and make inference from it will be the foundation for the new quantification framework. To achieve the holistic genomic privacy objective, cryptographic tools, techniques from information theory, and statistics (differential privacy) will be used.
This project will be a significant step towards understanding the privacy risks on genomic data of individuals and protecting the privacy of genomic data. It will also provide a new vision for security and privacy of health-related data in general and will find many implications in other domains such as banking and online social networks. The results of the project will also have an impact on future policies and legislation about protection of health-related data.
This EF will have big impact on the future career of the applicant by helping him build new connections, enhance his expertise, increase his visibility in the field of security and privacy, and improve his independent research skills.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2018 |
Nora von Thenen, Erman Ayday, A Ercument Cicek Re-identification of individuals in genomic data-sharing beacons via allele inference published pages: , ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty643 |
Bioinformatics | 2019-06-13 |
| 2017 |
Mathias Humbert, Erman Ayday, Jean-Pierre Hubaux, Amalio Telenti Quantifying Interdependent Risks in Genomic Privacy published pages: 1-31, ISSN: 2471-2566, DOI: 10.1145/3035538 |
ACM Transactions on Privacy and Security 20/1 | 2019-06-13 |
| 2017 |
Nora von Thenen, Erman Ayday, Ercument Cicek Inference Attacks Against Genomic Data-Sharing Beacons published pages: , ISSN: , DOI: |
2019-06-13 | |
| 2017 |
Erman Ayday, Mathias Humbert Inference Attacks against Kin Genomic Privacy published pages: 29-37, ISSN: 1540-7993, DOI: 10.1109/MSP.2017.3681052 |
IEEE Security & Privacy 15/5 | 2019-06-13 |
| 2016 |
Erman Ayday Cryptographic Solutions for Genomic Privacy published pages: 328-341, ISSN: , DOI: 10.1007/978-3-662-53357-4_22 |
Financial Cryptography and Data Security | 2019-06-13 |
| 2017 |
Anisa Halimi, Erman Ayday Profile Matching Across Unstructured Online Social Networks: Threats and Countermeasures published pages: , ISSN: , DOI: |
2019-06-13 | |
| 2016 |
Volkan Kucuk, Erman Ayday Profile Matching Across Unstructured Online Social Networks published pages: , ISSN: , DOI: |
2019-06-13 | |
| 2018 |
Iman Deznabi, Mohammad Mobayen, Nazanin Jafari, Oznur Tastan, Erman Ayday An Inference Attack on Genomic Data Using Kinship, Complex Correlations, and Phenotype Information published pages: 1333-1343, ISSN: 1545-5963, DOI: 10.1109/TCBB.2017.2709740 |
IEEE/ACM Transactions on Computational Biology and Bioinformatics 15/4 | 2019-06-13 |
| 2016 |
Zhicong Huang, Erman Ayday, Huang Lin, Raeka S. Aiyar, Adam Molyneaux, Zhenyu Xu, Jacques Fellay, Lars M. Steinmetz, Jean-Pierre Hubaux A privacy-preserving solution for compressed storage and selective retrieval of genomic data published pages: 1687-1696, ISSN: 1088-9051, DOI: 10.1101/gr.206870.116 |
Genome Research 26/12 | 2019-06-13 |
| 2017 |
Gulce Kale, Erman Ayday, Oznur Tastan A utility maximizing and privacy preserving approach for protecting kinship in genomic databases published pages: 181-189, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btx568 |
Bioinformatics 34/2 | 2019-06-13 |
| 2017 |
Erman Ayday, Qiang Tang, Arif Yilmaz Cryptographic Solutions for Credibility and Liability Issues of Genomic Data published pages: 1-1, ISSN: 1545-5971, DOI: 10.1109/TDSC.2017.2690422 |
IEEE Transactions on Dependable and Secure Computing | 2019-06-13 |
| 2017 |
Arif Yilmaz, Erman Ayday Collusion-Secure Watermarking for Sequential Data published pages: , ISSN: , DOI: |
2019-06-13 |
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