Analyzing the Privacy and Societal Challenges Stemming from the Rise of Personal Genomic Testing

Progress in genomics is enabling researchers to better understand the role of the genome in our health and well-being, stimulating hope for more effective and cost efficient healthcare. At the same time, the rapid cost drop of genome sequencing has enabled the emergence of a booming market for direct-to-consumer (DTC) genetic testing. Nowadays, companies like 23andMe and AncestryDNA provide affordable health, genealogy, and ancestry reports, and have already tested tens of millions of customers. How- ever, while this technology has the potential to transform society by improving people’s lives, it also harbors dangers as it prompts important privacy and societal concerns. In this thesis, we shed light on these issues using a mixed-methods approach. We start by conducting a technical investigation of the limitations on privacy-enhancing technologies used for testing, storing, and sharing genomic data. We rely on a structured methodology to contextualize and provide a critical analysis of the current state-of-the-art and we identify and discuss ten open problems faced by the community. We then focus on the societal aspects of DTC genetic testing by conducting two large-scale analyses of the genetic testing discourse focusing on both mainstream and fringe social networks, specifically, Twitter, Reddit, and 4chan. Our analyses show that DTC genetic testing is a popular topic of discussion on all platforms. However, these discussions often include highly toxic language expressed through hateful and racist comments and openly antisemitic rhetoric, often conveyed through memes. Overall, our findings highlight that the rise in popularity of this new technology is accompanied by several societal implications that are unlikely to be addressed by only one research field and rather require a multi-disciplinary approach

Systematizing Genome Privacy Research: A Privacy-Enhancing Technologies Perspective

Rapid advances in human genomics are enabling researchers to gain a better understanding of the role of the genome in our health and well-being, stimulating hope for more effective and cost efficient healthcare. However, this also prompts a number of security and privacy concerns stemming from the distinctive characteristics of genomic data. To address them, a new research community has emerged and produced a large number of publications and initiatives. In this paper, we rely on a structured methodology to contextualize and provide a critical analysis of the current knowledge on privacy-enhancing technologies used for testing, storing, and sharing genomic data, using a representative sample of the work published in the past decade. We identify and discuss limitations, technical challenges, and issues faced by the community, focusing in particular on those that are inherently tied to the nature of the problem and are harder for the community alone to address. Finally, we report on the importance and difficulty of the identified challenges based on an online survey of genome data privacy expertsComment: To appear in the Proceedings on Privacy Enhancing Technologies (PoPETs), Vol. 2019, Issue

"And We Will Fight For Our Race!" A Measurement Study of Genetic Testing Conversations on Reddit and 4chan

Rapid progress in genomics has enabled a thriving market for “direct-to-consumer” genetic testing, whereby people have access to their genetic information without the involvement of a healthcare provider. Companies like 23andMe and AncestryDNA, which provide affordable health, genealogy, and ancestry reports, have already tested tens of millions of customers. At the same time, alas, far-right groups have also taken an interest in genetic testing, using them to attack minorities and prove their genetic “purity.” However, the relation between genetic testing and online hate has not really been studied by the scientific community. To address this gap, we present a measurement study shedding light on how genetic testing is discussed on Web communities in Reddit and 4chan. We collect 1.3M comments posted over 27 months using a set of 280 keywords related to genetic testing. We then use Latent Dirichlet Allocation, Google’s Perspective API, Perceptual Hashing, and word embeddings to identify trends, themes, and topics of discussion. Our analysis shows that genetic testing is discussed frequently on Reddit and 4chan, and often includes highly toxic language expressed through hateful, racist, and misogynistic comments. In particular, on 4chan’s politically incorrect board (/pol/), content from genetic testing conversations involves several alt-right personalities and openly antisemitic memes. Finally, we find that genetic testing appears in a few unexpected contexts, and that users seem to build groups ranging from technology enthusiasts to communities using it to promote fringe political views

Lightweight oblivious transfer extensions

Η ασφαλής πολυκομματική υπολογιστική (Secure Multiparty Computation) (MPC) δημιουργήθηκε από τον A. Yao το 1962. Παρόλο που τότε αποτελούσε μόνο ένα θεωρητικό πρόβλημα, σήμερα, λόγω του Υπολογιστικού Νέφους (Cloud Computing) το οποίο είναι η νέα μόδα στην πληροφορική και στη διαχείριση πόρων, η ανάγκη για την ασφαλή πολυκομματική υπολογιστική είναι μεγαλύτερη από ποτέ. Ένα από τα σημαντικότερα κρυπτογραφικά πρωτόγονα εργαλεία (primitives) είναι για το MPC είναι το πρωτόκολλο Oblivious Transfer, το οποίο είναι διαβόητο για την μεγάλη κατανάλωση υπολογιστικών πόρων, λόγω του γεγονότος ότι χρησιμοποιεί κρυπτογράφηση δημοσίου κλειδιού. Για αυτούς τους λόγους, είναι εξαιρετικά σημαντικό να επενδύσουμε σε νέους, πιο πρακτικούς τρόπους υλοποίησης του Oblivious Transfer πρωτοκόλλου. Η απάντηση σε αυτή την έκκληση ονομάζεται Oblivious Transfer Extensions (OTE). Σε αυτή την διπλωματική εργασία, εξετάζουμε την κατηγορία της ασφαλούς πολυκομματικής υπολογιστικής, ερευνούμε τον τρόπο με τον οποίο τα Oblivious Transfer και Oblivious Transfer Extension πρωτόκολλα λειτουργούν και υλοποιούμε το πιο σημαντικό Oblivious Transfer Extension, υπό το όνομα IKPN03, το οποίο δημιουργήθηκε από τους Yuval Ishai, Joe Kilian, Kobbi Nissim και Erez Petrank, χρησιμοποιώντας την γλώσσα προγραμματισμού Java και την βιβλιοθήκη SCAPI. Ο σκοπός της εργασίας είναι να κατανοήσουμε τις διάφορες πτυχές των συγκεκριμένων πρωτοκόλλων και να αναγνωρίσουμε τυχόν προβλήματα, καθώς και να προτείνουμε νέες κατευθύνσεις για έρευνα