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Recent data protection regulations (notably, GDPR and CCPA) grant consumers various rights, including the right to access, modify or delete any personal information collected about them (and retained) by a service provider. To exercise these rights, one must submit a verifiable consumer request proving that the collected data indeed pertains to them. This action is straightforward for consumers with active accounts with a service provider at the time of data collection, since they can use standard (e.g., password-based) means of authentication to validate their requests. However, a major conundrum arises from the need to support consumers without accounts to exercise their rights. To this end, some service providers began requiring such accountless consumers to reveal and prove their identities (e.g., using government-issued documents, utility bills, or credit card numbers) as part of issuing a verifiable consumer request. While understandable as a short-term fix, this approach is cumbersome and expensive for service providers as well as privacy-invasive for consumers. Consequently, there is a strong need to provide better means of authenticating requests from accountless consumers. To achieve this, we propose VICEROY, a privacy-preserving and scalable framework for producing proofs of data ownership, which form a basis for verifiable consumer requests. Building upon existing web techniques and features, VICEROY allows accountless consumers to interact with service providers, and later prove that they are the same person in a privacy-preserving manner, while requiring minimal changes for both parties. We design and implement VICEROY with emphasis on security/privacy, deployability and usability. We also assess its practicality via extensive experiments.
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PIVA: Privacy-Preserving Identity Verification Methods for Accountless Users via Private List Intersection and Variants
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.
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- Award ID(s):
- 2030575
- PAR ID:
- 10616407
- Editor(s):
- Garcia-Alfaro, J; Kozik, R; Choraś, M; Katsikas, S
- Publisher / Repository:
- Springer Nature Switzerland
- Date Published:
- Page Range / eLocation ID:
- 362 to 382
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Book Chapter:
- https://doi.org/10.1007/978-3-031-70896-1_18
