Streaming and Unbalanced PSI from Function Secret Sharing

Dittmer, Samuel; Ishai, Yuval; Lu, Steve; Ostrovsky, Rafail; Elsabagh, Mohamed; Kiourtis, Nikolaos; Schulte, Brian; Stavrou, Angelos

doi:10.1007/978-3-031-14791-3_25

Cited by 6 publications

(17 citation statements)

References 33 publications

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“…We refer the reader to [17] for additional discussion and motivation of PSI. Recently, private contact tracing applications related to COVID‐19 [6, 8, 9, 14] found PSI‐CA as the ultimate cryptographic tool, allowing multiple participants (users and healthcare providers) to privately match contact information and notify users who may have been infected. In this work, we mainly focus on a variant of PSI problems, PSI‐CA.…”

Section: Related Workmentioning

confidence: 99%

“…However, Catalic system requires at least two non‐colluding cloud servers with a heavy computation/communication cost of Odk‐PRF. In addition, the underlying OPRF of Odk‐PRF is based on Oblivious Transfer [21], which is not deployment‐friendly. Function Secret Sharing (FSS) based PSI‐CA [8]: Dittmer et al. [8] introduces a variant of PSI‐CA (so‐called weighted PSI‐CA) in which each token of the client has an associated secret weight.…”

Section: Related Workmentioning

confidence: 99%

“…In addition, the underlying OPRF of Odk‐PRF is based on Oblivious Transfer [21], which is not deployment‐friendly. Function Secret Sharing (FSS) based PSI‐CA [8]: Dittmer et al. [8] introduces a variant of PSI‐CA (so‐called weighted PSI‐CA) in which each token of the client has an associated secret weight. The weight indicates a proximity estimate (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…Function Secret Sharing (FSS) based PSI‐CA [8]: Dittmer et al. [8] introduces a variant of PSI‐CA (so‐called weighted PSI‐CA) in which each token of the client has an associated secret weight. The weight indicates a proximity estimate (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…By keeping track of when and where they received which tokens, authors in [7] can identify the travel route of the individuals. To prevent the linkage attack, prior work [8, 9] relies on private set intersection cardinality (PSI‐CA), which is used to check how many tokens held by a user match the tokens in a set stored on a server without the users revealing their tokens. In this work, we propose a more efficient PSI‐CA protocol, which can be integrated into a contact tracing system to improve the system's performance.…”

Section: Introductionmentioning

confidence: 99%

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Secure contact tracing platform from simplest private set intersection cardinality

Gao

Surana

Trieu

2022

IET Information Security

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Contact tracing is an essential tool for controlling the spread of disease through human populations. However, existing contact tracing applications are either vulnerable to privacy and security attacks or heavy bandwidth/computational requirements on the client's devices. In this work, we introduce SecureCT, a Secure Contact Tracing platform with strong privacy protection and lightweight cost. SecureCT prevents linkage attacks, eliminates replay and relay attacks, and allows the phone's holder to delegate their contact tracing computation to untrusted servers while maintaining the user's privacy. The technical core of our scheme is an efficient Private Set Intersection Cardinality protocol which only relies on symmetric-key primitives. We evaluate its performance to show the feasibility of our proposed system in practice.

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Section: Related Workmentioning

confidence: 99%