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Subject: [digest] 2024 Week 49
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## In this issue

1. [2024/879] Consistency-or-Die: Consistency for Key Transparency
2. [2024/886] A New Security Evaluation Method Based on Resultant ...
3. [2024/1948] ARK: Adaptive Rotation Key Management for Fully ...
4. [2024/1949] Avenger Ensemble: Genetic Algorithm-Driven Ensemble ...
5. [2024/1950] Two-Round 2PC ECDSA at the Cost of 1 OLE
6. [2024/1951] Vote&Check: Secure Postal Voting with Reduced Trust ...
7. [2024/1952] Worst-Case Lattice Sampler with Truncated Gadgets ...
8. [2024/1953] Truncation Untangled: Scaling Fixed-Point ...
9. [2024/1954] A Complete Characterization of One-More Assumptions ...
10. [2024/1955] Gold OPRF: Post-Quantum Oblivious Power Residue PRF
11. [2024/1956] MultiReg-FE: Registered FE for Unbounded Inner- ...
12. [2024/1957] NICE-PAKE: On the Security of KEM-Based PAKE ...
13. [2024/1958] M-Sel: A Message Selection Functional Encryption ...
14. [2024/1959] SoK: Privacy-Preserving Transactions in Blockchains
15. [2024/1960] Share the MAYO: thresholdizing MAYO
16. [2024/1961] On the (Im)possibility of Game-Theoretically Fair ...
17. [2024/1962] uKNIT: Breaking Round-alignment for Cipher Design ...
18. [2024/1963] Proof of Time: A Method for Verifiable Temporal ...
19. [2024/1964] Lova: Lattice-Based Folding Scheme from ...
20. [2024/1965] Onion Franking: Abuse Reports for Mix-Based Private ...
21. [2024/1966] Efficient Succinct Zero-Knowledge Arguments in the ...
22. [2024/1967] Analysis of REDOG: The Pad Thai Attack
23. [2024/1968] SoK: Pseudorandom Generation for Masked ...
24. [2024/1969] SoK: Security of the Ascon Modes
25. [2024/1970] Scribe: Low-memory SNARKs via Read-Write Streaming
26. [2024/1971] Further Connections Between Isogenies of ...
27. [2024/1972] RoK, Paper, SISsors =E2=80=93 Toolkit for Lattice-based ...

## 2024/879

* Title: Consistency-or-Die: Consistency for Key Transparency
* Authors: Joakim Brorsson, Elena Pagnin, Bernardo David, Paul Stankovski Wag=
ner
* [Permalink](https://eprint.iacr.org/2024/879)
* [Download](https://eprint.iacr.org/2024/879.pdf)

### Abstract

This paper proposes a new consistency protocol that protects a key transparen=
cy log against split-view attacks and - contrary to all previous work - does =
not to rely on small committees of known external auditors, or out-of-band ch=
annels, or blockchains (full broadcast systems).

Our approach is to use a mechanism for cryptographically selecting a small co=
mmittee of random and initially undisclosed users, which are then tasked to e=
ndorse the current view of the log. The name of our protocol, Consistency-or-=
Die (CoD), reflects that users are guaranteed to know if they are in a consis=
tent state or not, and upon spotting an inconsistency in the key transparency=
 log, users stop using this resource and become inactive (die). CoD relies on=
 well-established cryptographic building blocks, such as verifiable random fu=
nctions and key-evolving signatures, for which lightweight constructions exis=
t. We provide a novel statistical analysis for identifying optimal quorum siz=
es (minimal number of endorsers for a view) for various security levels and p=
ercentages of malicious users.

Our experiments support that CoD is practical and can run in the background o=
n mid-tier smart phones, for large-scale systems with billions of users.



## 2024/886

* Title: A New Security Evaluation Method Based on Resultant for Arithmetic-O=
riented Algorithms
* Authors: Hong-Sen Yang, Qun-Xiong Zheng, Jing Yang, Quan-feng Liu, Deng Tang
* [Permalink](https://eprint.iacr.org/2024/886)
* [Download](https://eprint.iacr.org/2024/886.pdf)

### Abstract

The rapid development of advanced cryptographic applications like multi-party=
 computation (MPC), fully homomorphic encryption (FHE), and zero-knowledge (Z=
K) proofs have motivated the designs of the so-called arithmetic-oriented (AO=
) primitives. Efficient AO primitives typically build over large fields and u=
se large S-boxes. Such design philosophy brings difficulties in the cryptanal=
ysis of these primitives as classical cryptanalysis methods do not apply well=
.. The generally recognized attacks against these primitives are algebraic att=
acks, especially Groebner basis attacks. Thus, the numbers of security rounds=
 are usually derived through the complexity of solving the system of algebrai=
c equations using Groebner bases. In this paper, we propose a novel framework=
 for algebraic attacks against AO primitives. Instead of using Groebner basis=
, we use resultants to solve a system of multivariate equations that can bett=
er exploit the algebraic structures of AO primitives. We employ several techn=
iques to reduce the dimensions of the resultants and avoid rapid increases in=
 degrees, including meet-in-the-middle modeling, variable substitutions, and =
fast Lagrange interpolation. We apply our attack to three mainstream AO crypt=
ographic primitives: Rescue-Prime, Anemoi, and Jarvis. For Rescue-Prime, we t=
heoretically prove that the final univariate equation has a degree of at most=
 a specific power of three and practically attack five rounds for the first t=
ime. We attack the full-round of Anemoi with complexity 2^110.10, which has b=
een claimed to provide 127 bits of security. We also give the first practical=
 attack against eight rounds of Anemoi over a 55-bit prime field. For Jarvis,=
 we improve the existing practical attack by a factor of 100. Therefore, we p=
oint out that our analysis framework can be used as a new evaluation method f=
or AO designs.



## 2024/1948

* Title: ARK: Adaptive Rotation Key Management for Fully Homomorphic Encrypti=
on Targeting Memory Efficient Deep Learning Inference
* Authors: Jia-Lin Chan, Wai-Kong Lee, Denis C.-K Wong, Wun-She Yap, Bok-Min =
Goi
* [Permalink](https://eprint.iacr.org/2024/1948)
* [Download](https://eprint.iacr.org/2024/1948.pdf)

### Abstract

Advancements in deep learning (DL) not only revolutionized many aspects in ou=
r lives, but also introduced privacy concerns, because it processed vast amou=
nts of information that was closely related to our daily life. Fully Homomorp=
hic Encryption (FHE) is one of the promising solutions to this privacy issue,=
 as it allows computations to be carried out directly on the encrypted data. =
However, FHE requires high computational cost, which is a huge barrier to its=
 widespread adoption. Many prior works proposed techniques to enhance the spe=
ed performance of FHE in the past decade, but they often impose significant m=
emory requirements, which may be up to hundreds of gigabytes. Recently, focus=
 has shifted from purely improving speed performance to managing FHE=E2=80=99=
s memory consumption as a critical challenge. Rovida and Leporati introduced =
a technique to minimize rotation key memory by retaining only essential keys,=
 yet this technique is limited to cases with symmetric numerical patterns (e.=
g., -2 -1 0 1 2), constraining its broader utility. In this paper, a new tech=
nique, Adaptive Rotation Key (ARK), is proposed that minimizes rotation key m=
emory consumption by exhaustively analyzing numerical patterns to produce a m=
inimal subset of shared rotation keys. ARK also provides a dual-configuration=
 option, enabling users to prioritize memory efficiency or computational spee=
d. In memory-prioritized mode, ARK reduces rotation key memory consumption by=
 41.17% with a 12.57% increase in execution time. For speed-prioritized mode,=
 it achieves a 24.62% rotation key memory reduction with only a 0.21% impact =
on execution time. This flexibility positions ARK as an effective solution fo=
r optimizing FHE across varied use cases, marking a significant advancement i=
n optimization strategies for FHE-based privacy-preserving systems.



## 2024/1949

* Title: Avenger Ensemble: Genetic Algorithm-Driven Ensemble Selection for De=
ep Learning-based Side-Channel Analysis
* Authors: Zhao Minghui, Trevor Yap
* [Permalink](https://eprint.iacr.org/2024/1949)
* [Download](https://eprint.iacr.org/2024/1949.pdf)

### Abstract

Side-Channel Analysis (SCA) exploits physical vulnerabilities in systems to r=
eveal secret keys. With the rise of Internet-of-Things, evaluating SCA attack=
s has become crucial. Profiling attacks, enhanced by Deep Learning-based Side=
-Channel Analysis (DLSCA), have shown significant improvements over classical=
 techniques. Recent works demonstrate that ensemble methods outperform single=
 neural networks. However, almost every existing ensemble selection method in=
 SCA only picks the top few best-performing neural networks for the ensemble,=
 which we coined as Greedily-Selected Method (GSM), which may not be optimal.
This work proposes Evolutionary Avenger Initiative (EAI), a genetic algorithm=
-driven ensemble selection algorithm, to create effective ensembles for DLSCA=
.. We investigate two fitness functions and evaluate EAI across four datasets,=
 including \AES and \ascon implementations. We show that EAI outperforms GSM,=
 recovering secrets with the least number of traces. Notably, EAI successfull=
y recovers secret keys for \ascon datasets where GSM fails, demonstrating its=
 effectiveness.



## 2024/1950

* Title: Two-Round 2PC ECDSA at the Cost of 1 OLE
* Authors: Michael Adjedj, Constantin Blokh, Geoffroy Couteau, Antoine Joux, =
Nikolaos Makriyannis
* [Permalink](https://eprint.iacr.org/2024/1950)
* [Download](https://eprint.iacr.org/2024/1950.pdf)

### Abstract

We present a novel protocol for two-party ECDSA that achieves two rounds (a s=
ingle back-and-forth communication) at the cost of a single oblivious linear =
function evaluation (OLE). In comparison, the previous work of [DKLs18] (S&P =
2018) achieves two rounds at the cost of three OLEs, while [BHL24] (Manuscrip=
t 2024) requires expensive zero-knowledge proofs on top of the OLE. We demons=
trate this by proving that in the generic group model, any adversary capable =
of generating forgeries for our protocol can be transformed into an adversary=
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