Fuzzy Message Detection

Beck, Gabrielle; Len, Julia; Miers, Ian; Green, Matthew

doi:10.1145/3460120.3484545

Cited by 9 publications

(14 citation statements)

References 31 publications

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“…In the first construction (in Section 6.2), we take a similar approach as FMD from [BLMG21]. But we reduce its overhead from O(λ) to 1 bit per signal by making novel use of ciphertext compression techniques [BDGM19].…”

Section: Our Contributionsmentioning

confidence: 99%

“…But we reduce its overhead from O(λ) to 1 bit per signal by making novel use of ciphertext compression techniques [BDGM19]. Additionally, we show how to allow finer false-positive rates without requiring heavy tools like garbled circuits as in [BLMG21].…”

Section: Our Contributionsmentioning

confidence: 99%

“…We then present a new scalable framework for fuzzy tracking (in Section 4.4) followed by an efficient construction (in Section 6.3) in the random oracle model. This framework can be viewed as a 'dual' version of FMD mechanism from [BLMG21]. Intuitively, it is a trade-off between efficiency and usability: By limiting the users' ability to choose false-positive rates, we are able to reduce the tracking server's computational work to an amount which is sublinear in the total number of users.…”

Section: Our Contributionsmentioning

confidence: 99%

“…We will now turn to the issue that in the above constructions, the tracking mechanism will leak the users' metadata to the tracking servers, i.e., the tracking server will know exactly which mtk belongs to which specific (opk, tki). As discussed above, to address this problem, Beck et al [BLMG21] proposed a mechanism named fuzzy message detection (FMD): The server is given a fuzzy tracking key ftk instead of mtk to filter incoming fuzzy tracking information ftki for its users. Here, ftki is attached with (opk, tki).…”

Section: Fuzzy Trackingmentioning

confidence: 99%

“…A downside of the above tracking method is that we fully give up anonymity/unlinkability with regards to the tracking server who learns exactly which payments are addressed to the recipient. While there is a natural and obvious tension between the anonymity goal of unlinkability and functional goal of trackability, a recent work of Beck et al [BLMG21] attempts to strike a balance between these notions. They introduce the concept of fuzzy message detection (FMD), where a tracking server can approximately detect messages meant for a recipient with adjustable degree of uncertainty.…”

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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: Our Contributionsmentioning

confidence: 99%

Section: Our Contributionsmentioning

confidence: 99%

Section: Our Contributionsmentioning

confidence: 99%

Section: Fuzzy Trackingmentioning

confidence: 99%

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confidence: 99%

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