The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees?

Seres, István András; Pejó, Balázs; Burcsi, Péter

doi:10.1007/978-3-031-18283-9_7

Cited by 4 publications

(8 citation statements)

References 28 publications

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“…Instead, it is fixed in advance in this setting. This weakening is reasonable as it was shown in [SPB21] that an adversary can mount statistical attacks if users have varying false positive rates. To circumvent such attacks it was suggested that all users have high enough false positivity rates as even a small subset of low rate users can affect unlinkability for the entire pool of users.…”

Section: Scalable Fuzzy Trackingmentioning

confidence: 87%

“…Therefore we can fix the false positivity rate to be a high enough value for everyone. For example, as calculated in [SPB21], the false-positive rate ρ is better to be as large as 1 √ N…”

Section: Scalable Fuzzy Trackingmentioning

confidence: 97%

“…All these works assume a semi-honest server, except for Π TEE , which also considers a malicious server. Note that for security, ρ needs to be as large as 1 √ N as calculated in [SPB21]. Additionally, some prior works consider fuzzy schemes ([BLMG21] and ours) as ρM -anonymity, where M is the total number of messages.…”

Section: B Performance Analysismentioning

confidence: 99%

“…Additionally, some prior works consider fuzzy schemes ([BLMG21] and ours) as ρM -anonymity, where M is the total number of messages. However, this is not accurate due to statistical attacks as shown in [SPB21]: even with only one message (M = 1), some extent of anonymity is maintained if N is large.…”

Section: B Performance Analysismentioning

confidence: 99%

“…According to[SPB21], "concerning recipient unlinkability and temporal detection ambiguity, the false-positive rate needs to be high and there must be a large number of users in the system." This can be achieved in current blockchain systems with millions of users by setting the false-positive rate to be 1/ √ N .…”

mentioning

confidence: 99%

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Post Quantum Fuzzy Stealth Signatures and Applications

Pu,

Thyagarajan,

Döttling

et al. 2023

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

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Private payments in blockchain-based cryptocurrencies have been a topic of research, both academic and industrial, ever since the advent of Bitcoin. Stealth address payments were proposed as a solution to improve payment privacy for users and are, in fact, deployed in several major cryptocurrencies today. The mechanism lets users receive payments so that none of these payments are linkable to each other or the recipient. Currently known stealth address mechanisms either (1) are insecure in certain reasonable adversarial models, (2) are inefficient in practice or (3) are incompatible with many existing currencies.In this work, we formalize the underlying cryptographic abstraction of this mechanism, namely, stealth signatures with formal game-based definitions. We show a surprising application of our notions to passwordless authentication defined in the Fast IDentity Online (FIDO) standard. We then present Spirit, the first efficient post-quantum secure stealth signature construction based on the NIST standardized signature and key-encapsulation schemes, Dilithium and Kyber. The basic form of Spirit is only secure in a weak security model, but we provide an efficiencypreserving and generic transform, which boosts the security of Spirit to guarantee the strongest security notion defined in this work. Compared to state-of-the-art, there is an approximately 800x improvement on the signature size while keeping signing and verification as efficient as 0.2 ms.We extend Spirit with a fuzzy tracking functionality where recipients can outsource the tracking of incoming transactions to a tracking server, satisfying an anonymity notion similar to that of fuzzy message detection (FMD) recently introduced in [CCS 2021]. We also extend Spirit with a new fuzzy tracking framework called scalable fuzzy tracking that we introduce in this work. This new framework can be considered as a dual of FMD, in that it reduces the tracking server's computational workload to sublinear in the number of users, as opposed to linear in FMD. Experimental results show that, for millions of users, the server only needs 3.4 ms to filter each incoming message which is a significant improvement upon the state-of-the-art.

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Section: Scalable Fuzzy Trackingmentioning

confidence: 87%

Section: Scalable Fuzzy Trackingmentioning

confidence: 97%

Section: B Performance Analysismentioning

confidence: 99%

Section: B Performance Analysismentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Post Quantum Fuzzy Stealth Signatures and Applications

Pu,

Thyagarajan,

Döttling

et al. 2023

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

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Anonymity Analysis of the Umbra Stealth Address Scheme on Ethereum

Kovács,

Seres

2024

Companion Proceedings of the ACM Web Conference 2024

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Blockchain-Based, Confidentiality-Preserving Orchestration of Collaborative Workflows

Toldi,

Kocsis

2023

Infocommunications journal

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Business process collaboration between independent parties is challenging when participants do not completely trust each other. Tracking actions and enforcing the activity authorizations of participants via blockchain-hosted smart contracts is an emerging solution to this lack of trust, with most state-of-the-art approaches generating the orchestrating smart contract logic from Business Process Model and Notation (BPMN) models. However, compared to centralized business process orchestration services, smart contract state typically leaks potentially sensitive information about the state of the collaboration, limiting the applicability of decentralized process orchestration. This paper presents a novel, collaboration confidentiality-preserving approach where the process orchestrator smart contract only stores encrypted and hashed process states and validates participant actions against a BPMN model using zero-knowledge proofs. We cover a subset of BPMN, which is sufficient from the practical point of view, support messagepassing between participants, and provide an open-source, endto-end prototype implementation that automatically generates the key software artifacts.

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The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees?

Cited by 4 publications

References 28 publications

Post Quantum Fuzzy Stealth Signatures and Applications

Post Quantum Fuzzy Stealth Signatures and Applications

Anonymity Analysis of the Umbra Stealth Address Scheme on Ethereum

Blockchain-Based, Confidentiality-Preserving Orchestration of Collaborative Workflows

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