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Several prominent privacy regulation (e.g., CCPA and GDPR) require service providers to let consumers request access to, correct, or delete, their personal data. Compliance necessitates verification of consumer identity. This is not a problem for consumers who already have an account with a service provider since they can authenticate themselves via a successful account log-in. However, there are no such methods for accountless consumers, even though service providers routinely collect data about casual consumers, i.e., those without accounts. Currently, in order to access their collected data, accountless consumers are asked to provide Personally Identifiable Information (PII) to service providers, which is privacy-invasive. To address this problem, we propose PIVA: Privacy-Preserving Identity Verification for Accountless Users, a technique based on Private List Intersection (PLI) and its variants. First, we introduce PLI, a close relative of private set intersection (PSI), a well-known cryptographic primitive that allows two or more mutually suspicious parties to compute the intersection of their private input sets. PLI takes advantage of the (ordered and fixed) list structure of each party’s private set. As a result, PLI is more efficient than PSI. We also explore PLI variants: PLI-cardinality (PLI-CA), threshold-PLI (t-PLI), and threshold-PLI-cardinality (t-PLI-CA), all of which yield less information than PLI. These variants are progressively better suited for addressing the accountless consumer authentication problem. We prototype and compare its performance against techniques based on regular PSI and garbled circuits (GCs). Results show that proposed PLI and PLI-CA constructions are more efficient than GC-based techniques, in terms of both computation and communication overheads. While GC-based t-PLI and t-PLI-CA execute faster, proposed constructs greatly outperform the former in terms of bandwidth, e.g., our t-PLI protocol consumes less bandwidth. We also show that proposed protocols can be made secure against malicious adversaries, with only moderate increases in overhead. These variants outperform their GC-based counterparts by at least one order of magnitude. 

Exciting recent advances in genome sequencing, coupled with greatly reduced storage and computation costs, make genomic testing increasingly accessible to individuals. Already today, one’s digitized DNA can be easily obtained from a sequencing lab and later used to conduct numerous tests by engaging with a testing facility. Due to the inherent sensitivity of genetic material and the often-proprietary nature of genomic tests, privacy is a natural and crucial issue. While genomic privacy received a great deal of attention within and outside the research community, genomic security has not been sufficiently studied. This is surprising since the usage of fake or altered genomes can have grave consequences, such as erroneous drug prescriptions and genetic test outcomes. Unfortunately, in the genomic domain, privacy and security (as often happens) are at odds with each other. In this article, we attempt to reconcile security with privacy in genomic testing by designing a novel technique for a secure and private genomic range query protocol between a genomic testing facility and an individual user. The proposed technique ensures authenticity and completeness of user-supplied genomic material while maintaining its privacy by releasing only the minimum thereof. To confirm its broad usability, we show how to apply the proposed technique to a previously proposed genomic private substring matching protocol. Experiments show that the proposed technique offers good performance and is quite practical. Furthermore, we generalize the genomic range query problem to sparse integer sets and discuss potential use cases.