GenoGuard: Protecting Genomic Data against Brute-Force Attacks Zhicong Huang, Erman Ayday, Jacques Fellay, Jean-Pierre Hubaux, Ari Juels Presented by Chuong.

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Presentation transcript:

GenoGuard: Protecting Genomic Data against Brute-Force Attacks Zhicong Huang, Erman Ayday, Jacques Fellay, Jean-Pierre Hubaux, Ari Juels Presented by Chuong Ngo

The Genomic Future

The Dangers of the Genomic Future

The Current Landscape

GenoGuard is honey encryption with n- gram derived seeds.

GenoGuard - System Model

Protection Mechanisms (e.g. encryption)

GenoGuard - System Model Protection Mechanisms (e.g. encryption) Authentication

GenoGuard - Protocol

GenoGuard - Encoding (0, 2) Single Nucleotide Variants Encoder Seed PBE Encrypted Seed

GenoGuard - Encoding 0 2

0 [0, 6)

GenoGuard - Encoding 0 2 [0.54, 6)

GenoGuard - Modeling Linkage disequilibrium and allele frequency K-th order Markov chains Recombination rates

Evaluation - Model Fitness

Evaluation - Storage Overhead

Evaluation - Experimental Security

Side Attacks - Ancestry Compatibility

Side Attacks - Hair Color

Side Attacks - Chromosomes

Conclusion

Discussion What are the potential weakness of GenoGuard? Does the use of Markov chains make sense? Why or why not? Do the authors claims of GenoGuard’s security make sense? Why or why not?