On the second-order zero differential spectra of some power functions over finite fields

Boukerrou et al. (IACR Trans. Symmetric Cryptol. 2020(1), 331-362) introduced the notion of Feistel Boomerang Connectivity Table (FBCT), the Feistel counterpart of the Boomerang Connectivity Table (BCT), and the Feistel boomerang uniformity (which is the same as the second-order zero differential uniformity in even characteristic). FBCT is a crucial table for the analysis of the resistance of block ciphers to power attacks such as differential and boomerang attacks. It is worth noting that the coefficients of FBCT are related to the second-order zero differential spectra of functions. In this paper, by carrying out certain finer manipulations of solving specific equations over the finite field $\mathbb{F}_{p^n}$, we explicitly determine the second-order zero differential spectra of some power functions with low differential uniformity, and show that our considered functions also have low second-order zero differential uniformity. Our study pushes further former investigations on second-order zero differential uniformity and Feistel boomerang differential uniformity for a power function $F$

On the Division Property of SIMON48 and SIMON64

{\sc Simon} is a family of lightweight block ciphers published by the U.S. National Security Agency (NSA) in 2013. Due to its novel and bit-based design, integral cryptanalysis on {\sc Simon} seems a tough job. At EUROCRYPT 2015 Todo proposed division property which is a generalized integral property, and he applied this technique to searching integral distinguishers of {\sc Simon} block ciphers by considering the left and right halves of {\sc Simon} independently. As a result, he found 11-round integral distinguishers for both {\sc Simon}48 and {\sc Simon}64. Recently, at FSE 2016 Todo \emph{et al.} proposed bit-based division property that considered each bit independently. This technique can find more accurate distinguishers, however, as pointed out by Todo \emph{et al.} the time and memory complexity is bounded by $2^n$ for an $n$-bit block cipher. Thus, bit-based division property is only applicable to {\sc Simon}32. In this paper we propose a new technique that achieves a trade-off between considering each bit independently and considering left and right halves as a whole, which is actually a trade-off between time-memory and the accuracy of the distinguishers. We proceed by splitting the state of {\sc Simon} into small pieces and study the division property propagations of circular shift and bitwise AND operations under the state partition. Moreover, we propose two different state partitions and study the influences of different partitions on the propagation of division property. We find that different partitions greatly impact the division property propagation of circular shift which will finally result in a big difference on the length of integral distinguishers. By using a tailored search algorithm for {\sc Simon}, we find 12-round integral distinguishers for {\sc Simon}48 and {\sc Simon}64 respectively, which improve Todo\u27s results by one round for both variants

On the Relationships between Different Methods for Degree Evaluation (Full Version)

In this paper, we compare several non-tight degree evaluation methods i.e., Boura and Canteaut\u27s formula, Carlet\u27s formula as well as Liu\u27s numeric mapping and division property proposed by Todo, and hope to find the best one from these methods for practical applications. Specifically, for the substitution-permutation-network (SPN) ciphers, we first deeply explore the relationships between division property of an Sbox and its algebraic properties (e.g., the algebraic degree of its inverse). Based on these findings, we can prove theoretically that division property is never worse than Boura and Canteaut\u27s and Carlet\u27s formulas, and we also experimentally verified that the division property can indeed give a better bound than the latter two methods. In addition, for the nonlinear feedback shift registers (NFSR) based ciphers, according to the propagation of division property and the core idea of numeric mapping, we give a strict proof that the estimated degree using division property is never greater than that of numeric mapping. Moreover, our experimental results on Trivium and Kreyvium indicate the division property actually derives a much better bound than the numeric mapping. To the best of our knowledge, this is the first time to give a formal discussion on the relationships between division property and other degree evaluation methods, and we present the first theoretical proof and give the experimental verification to illustrate that division property is the optimal one among these methods in terms of the accuracy of the upper bounds on algebraic degree

Ada-TTA: Towards Adaptive High-Quality Text-to-Talking Avatar Synthesis

We are interested in a novel task, namely low-resource text-to-talking avatar. Given only a few-minute-long talking person video with the audio track as the training data and arbitrary texts as the driving input, we aim to synthesize high-quality talking portrait videos corresponding to the input text. This task has broad application prospects in the digital human industry but has not been technically achieved yet due to two challenges: (1) It is challenging to mimic the timbre from out-of-domain audio for a traditional multi-speaker Text-to-Speech system. (2) It is hard to render high-fidelity and lip-synchronized talking avatars with limited training data. In this paper, we introduce Adaptive Text-to-Talking Avatar (Ada-TTA), which (1) designs a generic zero-shot multi-speaker TTS model that well disentangles the text content, timbre, and prosody; and (2) embraces recent advances in neural rendering to achieve realistic audio-driven talking face video generation. With these designs, our method overcomes the aforementioned two challenges and achieves to generate identity-preserving speech and realistic talking person video. Experiments demonstrate that our method could synthesize realistic, identity-preserving, and audio-visual synchronized talking avatar videos.Comment: 6 pages, 3 figure

GenerTTS: Pronunciation Disentanglement for Timbre and Style Generalization in Cross-Lingual Text-to-Speech

Cross-lingual timbre and style generalizable text-to-speech (TTS) aims to synthesize speech with a specific reference timbre or style that is never trained in the target language. It encounters the following challenges: 1) timbre and pronunciation are correlated since multilingual speech of a specific speaker is usually hard to obtain; 2) style and pronunciation are mixed because the speech style contains language-agnostic and language-specific parts. To address these challenges, we propose GenerTTS, which mainly includes the following works: 1) we elaborately design a HuBERT-based information bottleneck to disentangle timbre and pronunciation/style; 2) we minimize the mutual information between style and language to discard the language-specific information in the style embedding. The experiments indicate that GenerTTS outperforms baseline systems in terms of style similarity and pronunciation accuracy, and enables cross-lingual timbre and style generalization.Comment: Accepted by INTERSPEECH 202

StyleS2ST: Zero-shot Style Transfer for Direct Speech-to-speech Translation

Direct speech-to-speech translation (S2ST) has gradually become popular as it has many advantages compared with cascade S2ST. However, current research mainly focuses on the accuracy of semantic translation and ignores the speech style transfer from a source language to a target language. The lack of high-fidelity expressive parallel data makes such style transfer challenging, especially in more practical zero-shot scenarios. To solve this problem, we first build a parallel corpus using a multi-lingual multi-speaker text-to-speech synthesis (TTS) system and then propose the StyleS2ST model with cross-lingual speech style transfer ability based on a style adaptor on a direct S2ST system framework. Enabling continuous style space modeling of an acoustic model through parallel corpus training and non-parallel TTS data augmentation, StyleS2ST captures cross-lingual acoustic feature mapping from the source to the target language. Experiments show that StyleS2ST achieves good style similarity and naturalness in both in-set and out-of-set zero-shot scenarios.Comment: Accepted to Interspeech 202

Quantum Implementation and Resource Estimates for RECTANGLE and KNOT

With the advancement of the quantum computing technologies, a large body of research work is dedicated to revisit the security claims for ciphers being used. An adversary with access to a quantum computer can employ certain new attacks which would not be possible in the current pre-quantum era. In particular, the Grover\u27s search algorithm is a generic attack against symmetric key cryptographic primitives, that can reduce the search complexity to square root. To apply the Grover\u27s search algorithm, one needs to implement the target cipher as a quantum circuit. Although relatively recent, this field of research has attracted serious attention from the research community, as several ciphers (like AES, GIFT, SPECK, SIMON etc.) are being implemented as quantum circuits. In this work, we target the lightweight block cipher RECTANGLE and the Authenticated Encryption with Associated Data (AEAD) KNOT which is based on RECTANGLE; and implement those in the ProjectQ library (an open-source quantum compatible library designed by researchers from ETH Zurich). AEADs are considerably more complex to implement than a typical block/stream cipher, and ours is among the first works to do this