PPT-Inference and De-anonymization Attacks against Genomic Privacy

ETH Zürich October 1 2015 Mathias Humbert Joint work with Erman Ayday JeanPierre Hubaux Kévin Huguenin Joachim Hugonot Amalio Telenti Human System Security 0 1 0 0 1 1. Vitaly Shmatikov. Tastes and Purchases. slide . 2. Social Networks. slide . 3. Health Care and Genetics. slide . 4. Web Tracking. slide . 5. Solution: Anonymity!. “… breakthrough technology that uses social graph data to dramatically improve online marketing … . CS 656 Spring 2009. Should We Be Worried?. Medical Records Misuse. Burlington Northern allegedly conducted genetic tests on employees who had filed worker’s compensation claims for carpal tunnel syndrome, without their knowledge. The company’s intention was presumably to be able to reject some claims because of genetic predisposition to the condition.. Sam Weber. Software Engineering Institute, CMU. Thesis. Laws and regulations concerning data sharing and privacy often have unintended consequences. Problem Space. Three dimensions of issue:. What is ethical?. Zhicong Huang, Erman Ayday, Jacques Fellay, Jean-Pierre Hubaux, Ari Juels. Presented by Chuong Ngo. The Genomic Future. The Genomic Future. The Genomic Future. The Genomic Future. The Genomic Future. dem@ecs.soton.ac.uk. @. hoosfoos. PRIVACY: Part II. Managing Privacy. The System. Dealing with Privacy. Weitzner. DJ, Abelson H, Berners-Lee T, . Feigenbaum. J, . Sussman. . GJ. Information . Accountability. . via . Mining . GWAS S. tatistics . Yue. Wang, . Xintao. Wu and . Xinghua Shi. College of Computing and Informatics, . University of North Carolina at Charlotte . Background. Data . privacy in genome-wide association studies (GWAS) is . 1. University of Oklahoma -Tulsa. Aminmohammad Roozgard. , . Nafise Barzigar, . Dr. Pramode Verma, . Dr. Samuel Cheng. University of . O. klahoma - Tulsa. Today’s Presentation. Privacy concerns of releasing genomic data. John Krumm. Microsoft Research. Redmond, WA USA. Questions to Answer. Do . anonymized. location tracks reveal your identity?. If so, how much data corruption will protect you?. theory. experiment. Motivation – Why Send Your Location?. George Danezis (. g.danezis@ucl.ac.uk. ). With help from:. Luca . Melis (. luca.melis.14@ucl.ac.uk. ). Steve . Dodier-Lazaro (. s.dodier-lazaro.12@ucl.ac.uk. ). Why anonymize data?. Raw data – use cases:. Module 17 – Sharing Data While Preserving Privacy. some slides by Gen Bartlett. Jelena . Mirkovic. USC CSCI 430. Why Do We Want to Share?. Share existing data sets:. Research . Companies . Buy data from each other . . Data Privacy. Dr. Balaji Palanisamy. Associate Professor. School of Computing and Information. University of Pittsburgh. bpalan@pitt.edu. Slides Courtesy:. Prof. James Joshi (University of Pittsburgh).. Chi-Yin Chow. Department of Computer Science. City University of Hong Kong. Mohamed F. Mokbel. Department of Computer Science and Engineering. University of Minnesota . Outline. Introduction. Protecting Trajectory Privacy in Location-based Services. of sequences and its Application to Mobility Data Mining. Ruggero. . Pensa. , . Anna . Monreale. , Fabio . Pinelli. and Dino . Pedreschi. PILBA’0. 8 - . Workshop. , Oct . 9, 200. 8. , Malaga. Knowledge Discovery and Delivery Lab. Attacks. Chuan. Yue, chuanyue@mines.edu. IEEE . Workshop on Mobile Security Technologies (. MoST. ), . 2016. 1. 5/26/2016. Outline. Introduction and Background. Attacks. Potential Defense Mechanisms.