Reviewerly/exHarmony huggingface dataset:
An Incremental PoSW for General Weight Distributions

A proof of sequential work (PoSW) scheme allows the prover to convince a verifier that it computed a certain number of computational steps sequentially. Very recently, graph-labeling PoSW schemes, found applications in light-client blockchain protocols, most notably bootstrapping. A bootstrapping protocol allows a light client, with minimal information about the blockchain, to hold a commitment to its stable prefix. An incremental PoSW (iPoSW) scheme allows the prover to non-trivially increment proofs: given $$\chi ,\pi _1$$ and integers $$N_1,N_2$$ such that $$\pi _1$$ is a valid proof for $$N_1$$ , it generates a valid proof $$\pi $$ for $$N_1+N_2$$ . In this work, we construct an iPoSW scheme based on the skiplist-based PoSW scheme of Abusalah et al. and prove its security in the random oracle model by employing the powerful on-the-fly sampling technique of Döttling et al. Moreover, unlike the iPoSW scheme of Döttling et al., ours is the first iPoSW scheme which is suitable for constructing incremental non-interactive arguments of chain knowledge (SNACK) schemes, which are at the heart of space and time efficient blockchain light-client protocols. In particular, our scheme works for general weight distributions, which we characterize as incrementally sampleable distributions. Our general treatment recovers the distribution underlying the scheme of Döttling et al. as well as the distribution underlying SNACK-enabled bootstrapping application as special cases. In realizing our general construction, we develop a new on-the-fly sampling technique.
Witness-Succinct Universally-Composable SNARKs

Zero-knowledge Succinct Non-interactive ARguments of Knowledge (zkSNARKs) are becoming an increasingly fundamental tool in many real-world applications where the proof compactness is of the utmost importance, including blockchains. A proof of security for SNARKs in the Universal Composability (UC) framework (Canetti, FOCS'01) would rule out devastating malleability attacks. To retain security of SNARKs in the UC model, one must show their simulation-extractability such that the knowledge extractor is both black-box and straight-line, which would imply that proofs generated by honest provers are non-malleable. However, existing simulation-extractability results on SNARKs either lack some of these properties, or alternatively have to sacrifice witness succinctness to prove UC security. In this paper, we provide a compiler lifting any simulation-extractable NIZKAoK into a UC-secure one in the global random oracle model, importantly, while preserving the same level of witness succinctness. Combining this with existing zkSNARKs, we achieve, to the best of our knowledge, the first zkSNARKs simultaneously achieving UC-security and constant sized proofs.
Detect, Pack and Batch: Perfectly-Secure MPC with Linear Communication and Constant Expected Time

We prove that perfectly-secure optimally-resilient secure Multi-Party Computation (MPC) for a circuit with C gates and depth D can be obtained in $${\mathcal {O}}((Cn+n^4 + Dn^2)\log n)$$ communication complexity and $${\mathcal {O}}(D)$$ expected time. For $$D \ll n$$ and $$C\ge n^3$$ , this is the first perfectly-secure optimal-resilient MPC protocol with linear communication complexity per gate and constant expected time complexity per layer. Compared to state-of-the-art MPC protocols in the player elimination framework [Beerliova and Hirt TCC’08, and Goyal, Liu, and Song CRYPTO’19], for $$C>n^3$$ and $$D \ll n$$ , our results significantly improve the run time from $$\varTheta (n+D)$$ to expected $${\mathcal {O}}(D)$$ while keeping communication complexity at $${\mathcal {O}}(Cn\log n)$$ . Compared to state-of-the-art MPC protocols that obtain an expected $${\mathcal {O}}(D)$$ time complexity [Abraham, Asharov, and Yanai TCC’21], for $$C>n^3$$ , our results significantly improve the communication complexity from $${\mathcal {O}}(Cn^4\log n)$$ to $${\mathcal {O}}(Cn\log n)$$ while keeping the expected run time at $${\mathcal {O}}(D)$$ . One salient part of our technical contribution is centered around a new primitive we call detectable secret sharing. It is perfectly-hiding, weakly-binding, and has the property that either reconstruction succeeds, or $${\mathcal {O}}(n)$$ parties are (privately) detected. On the one hand, we show that detectable secret sharing is sufficiently powerful to generate multiplication triplets needed for MPC. On the other hand, we show how to share p secrets via detectable secret sharing with communication complexity of just $${\mathcal {O}}(n^4\log n+p \log n)$$ . When sharing $$p\ge n^4$$ secrets, the communication cost is amortized to just $${\mathcal {O}}(1)$$ per secret. Our second technical contribution is a new Verifiable Secret Sharing protocol that can share p secrets at just $${\mathcal {O}}(n^4\log n+pn\log n)$$ word complexity. When sharing $$p\ge n^3$$ secrets, the communication cost is amortized to just $${\mathcal {O}}(n)$$ per secret. The best prior required $${\mathcal {O}}(n^3)$$ communication per secret.
Unbounded Quadratic Functional Encryption and More from Pairings

We propose the first unbounded functional encryption (FE) scheme for quadratic functions and its extension, in which the sizes of messages to be encrypted are not a priori bounded. Prior to our work, all FE schemes for quadratic functions are bounded, meaning that the message length is fixed at the setup. In the first scheme, encryption takes $$\{x_{i}\}_{i \in S_{c}}$$ , key generation takes $$\{c_{i,j}\}_{i,j \in S_{k}}$$ , and decryption outputs $$\sum _{i,j \in S_{k}} c_{i,j}x_{i}x_{j}$$ if and only if $$S_{k} \subseteq S_{c}$$ , where the sizes of $$S_{c}$$ and $$S_{k}$$ can be arbitrary. Our second scheme is the extension of the first scheme to partially-hiding FE that computes an arithmetic branching program on a public input and a quadratic function on a private input. Concretely, encryption takes a public input $$\textbf{u}$$ in addition to $$\{x_{i}\}_{i \in S_{c}}$$ , a secret key is associated with arithmetic branching programs $$\{f_{i,j}\}_{i,j \in S_{k}}$$ , and decryption yields $$\sum _{i,j \in S_{k}} f_{i,j}(\textbf{u})x_{i}x_{j}$$ if and only if $$S_{k} \subseteq S_{c}$$ . Both our schemes are based on pairings and secure in the simulation-based model under the standard MDDH assumption.
Collision Attacks on Round-Reduced SHA-3 Using Conditional Internal Differentials

The KECCAK hash function was selected by NIST as the winner of the $$\texttt {SHA-3}$$ competition in 2012 and became the $$\texttt {SHA-3}$$ hash standard of NIST in 2015. On account of $$\texttt {SHA-3}$$ ’s importance in theory and applications, the analysis of its security has attracted increasing attention. In the $$\texttt {SHA-3}$$ family, $$\texttt {SHA3-512}$$ shows the strongest resistance against collision attacks: the theoretical attacks of $$\texttt {SHA3-512}$$ only extend to four rounds by solving polynomial systems with 64 times faster than the birthday attack. Yet for the $$\texttt {SHA-3}$$ instance SHAKE256 there are no results on collision attacks that we are aware of in the literatures. In this paper, we study the collision attacks against round-reduced $$\texttt {SHA-3}$$ . Inspired by the work of Dinur, Dunkelman and Shamir in 2013, we propose a variant of birthday attack and improve the internal differential cryptanalysis by abstracting new concepts such as differential transition conditions and difference conditions table. With the help of these techniques, we develop new collision attacks on round-reduced $$\texttt {SHA-3}$$ using conditional internal differentials. More exactly, the initial messages constrained by linear conditions pass through the first two rounds of internal differential, and their corresponding inputs entering the last two rounds are divided into different subsets for collision search according to the values of linear conditions. Together with an improved target internal difference algorithm (TIDA), collision attacks on up to 5 rounds of all the six $$\texttt {SHA-3}$$ functions are obtained. In particular, collision attacks on 4-round $$\texttt {SHA3-512}$$ and 5-round $$\texttt {SHAKE256}$$ are achieved with complexity of $$2^{237}$$ and $$2^{185}$$ respectively. As far as we know, this is the best collision attack on reduced $$\texttt {SHA3-512}$$ , and it is the first collision attack on reduced $$\texttt {SHAKE256}$$ .
Pitfalls and Shortcomings for Decompositions and Alignment

In this paper we, for the first time, study the question under which circumstances decomposing a round function of a Substitution-Permutation Network is possible uniquely. More precisely, we provide necessary and sufficient criteria for the non-linear layer on when a decomposition is unique. Our results in particular imply that, when cryptographically strong S-boxes are used, the decomposition is indeed unique. We then apply our findings to the notion of alignment, pointing out that the previous definition allows for primitives that are both aligned and unaligned simultaneously. As a second result, we present experimental data that shows that alignment might only have limited impact. For this, we compare aligned and unaligned versions of the cipher PRESENT.
Context Discovery and Commitment Attacks

A line of recent work has highlighted the importance of context commitment security, which asks that authenticated encryption with associated data (AEAD) schemes will not decrypt the same adversarially-chosen ciphertext under two different, adversarially-chosen contexts (secret key, associated data, and nonce). Despite a spate of recent attacks, many open questions remain around context commitment; most obviously nothing is known about the commitment security of important schemes such as CCM, EAX, and SIV. We resolve these open questions, and more. Our approach is to, first, introduce a new framework that helps us more granularly define context commitment security in terms of what portions of a context are adversarially controlled. We go on to formulate a new security notion, called context discoverability, which can be viewed as analogous to preimage resistance from the hashing literature. We show that unrestricted context commitment security (the adversary controls all of the two contexts) implies context discoverability security for a class of schemes encompassing most schemes used in practice. Then, we show new context discovery attacks against a wide set of AEAD schemes, including CCM, EAX, SIV, GCM, and OCB3, and, by our general result, this gives new unrestricted context commitment attacks against them. Finally, we explore the case of restricted context commitment security for the original SIV mode, for which no prior attack techniques work (including our context discovery based ones). We are nevertheless able to give a novel $$\mathcal {O}(2^{n/3})$$ attack using Wagner’s k-tree algorithm for the generalized birthday problem.
Analysis of RIPEMD-160: New Collision Attacks and Finding Characteristics with MILP

The hash function RIPEMD-160 is an ISO/IEC standard and is being used to generate the bitcoin address together with SHA-256. Despite the fact that many hash functions in the MD-SHA hash family have been broken, RIPEMD-160 remains secure and the best collision attack could only reach up to 34 out of 80 rounds, which was published at CRYPTO 2019. In this paper, we propose a new collision attack on RIPEMD-160 that can reach up to 36 rounds with time complexity $$2^{64.5}$$ . This new attack is facilitated by a new strategy to choose the message differences and new techniques to simultaneously handle the differential conditions on both branches. Moreover, different from all the previous work on RIPEMD-160, we utilize a MILP-based method to search for differential characteristics, where we construct a model to accurately describe the signed difference transitions through its round function. As far as we know, this is the first model targeting the signed difference transitions for the MD-SHA hash family. Indeed, we are more motivated to design this model by the fact that many automatic tools to search for such differential characteristics are not publicly available and implementing them from scratch is too time-consuming and difficult. Hence, we expect that this can be an alternative easy tool for future research, which only requires to write down some simple linear inequalities.
Generic Attack on Duplex-Based AEAD Modes Using Random Function Statistics

Duplex-based authenticated encryption modes with a sufficiently large key length are proven to be secure up to the birthday bound $$2^{\frac{c}{2}}$$ , where c is the capacity. However this bound is not known to be tight and the complexity of the best known generic attack, which is based on multicollisions, is much larger: it reaches $$\frac{2^c}{\alpha }$$ where $$\alpha $$ represents a small security loss factor. There is thus an uncertainty on the true extent of security beyond the bound $$2^{\frac{c}{2}}$$ provided by such constructions. In this paper, we describe a new generic attack against several duplex-based AEAD modes. Our attack leverages random functions statistics and produces a forgery in time complexity $$\mathcal {O}(2^{\frac{3c}{4}})$$ using negligible memory and no encryption queries. Furthermore, for some duplex-based modes, our attack recovers the secret key with a negligible amount of additional computations. Most notably, our attack breaks a security claim made by the designers of the NIST lightweight competition candidate Xoodyak. This attack is a step further towards determining the exact security provided by duplex-based constructions.
Black-Box Reusable NISC with Random Oracles

We revisit the problem of reusable non-interactive secure computation (NISC). A standard NISC protocol for a sender-receiver functionality f enables the receiver to encrypt its input x such that any sender, on input y, can send back a message revealing only f(x, y). Security should hold even when either party can be malicious. A reusable NISC protocol has the additional feature that the receiver's message can be safely reused for computing multiple outputs $$f(x,y_i)$$ . Here security should hold even when a malicious sender can learn partial information about the honest receiver's outputs in each session. We present the first reusable NISC protocol for general functions f that only makes a black-box use of any two-message oblivious transfer protocol, along with a random oracle. All previous reusable NISC protocols either made a non-black-box use of cryptographic primitives (Cachin et al. ICALP 2002) or alternatively required a stronger arithmetic variant of oblivious transfer and were restricted to f in $$\textsf{NC}^1$$ or similar classes (Chase et al. Crypto 2019). Our result is obtained via a general compiler from standard NISC to reusable NISC that makes use of special type of honest-majority protocols for secure multiparty computation. Finally, we extend the above main result to reusable two-sided NISC, in which two parties can encrypt their inputs in the first round and then reveal different functions of their inputs in multiple sessions. This extension either requires an additional (black-box) use of additively homomorphic commitment or alternatively requires the parties to maintain a state between sessions.
Comparison of Different Swarm Based Nature Inspired Algorithm for Solution of Optimization Problem

Optimization is a subproblem of different domains. It is a complex issue of today’s era for the solution to numerous problems. As a result, many ways are being used. Use of numerous Nature Inspired Algorithms in solving optimization problems has gained widespread appeal and acceptability in recent years. Due to their success in handling and generating good quality solutions for a variety of optimization issues, they become very famous. To find a solution we will use a general test benchmark. In this research, we take six different swarms based on naturally inspired algorithms and a comparison of them, such as Ant Colony Optimization, Particle Swarm Optimization, Grasshopper, Grey Wolf, Butterfly Optimization, and Cat Swarm Optimization, which was previously utilized to obtain an optimal solution. The comparison is based on various characteristics such as the nature of the algorithm, its convergence rate, accuracy, and the best solution. Efficient solution in less time is regularly an issue of these days where time efficient studies continue to it.
EVMTracer: Dynamic Analysis of the Parallelization and Redundancy Potential in the Ethereum Virtual Machine

Ethereum is one of the first blockchains executing smart contracts (financial applications directly executed on the ledger using a virtual machine).The performance of the Ethereum virtual machine has become a bottleneck caused by high volumes of transactions due to blockchain applications, including decentralized finance and non-fungible tokens.Hence, there is a need to detail the execution characteristics of the Ethereum virtual machine before its performance can be improved.This work introduces an off-line Ethereum virtual machine tracer called EVMTracer that produces runtime data dependence graphs from executed transactions as an alternative program representation.From the runtime dependence graphs, we can deduce valuable metrics about program execution characteristics, including the degree of parallelization and computational redundancies in smart contracts.Our experiments encompass all blocks up to 12 M on the Ethereum mainnet.We found a geometric mean of 1.90 × theoretical maximum speedup when executing the smart contracts in parallel and identified 34.97 % of SLOAD instructions as redundant.
Deniable Authentication When Signing Keys Leak

Deniable Authentication is a highly desirable property for secure messaging protocols: it allows a sender Alice to authentically transmit messages to a designated receiver Bob in such a way that only Bob gets convinced that Alice indeed sent these messages. In particular, it guarantees that even if Bob tries to convince a (non-designated) party Judy that Alice sent some message, and even if Bob gives Judy his own secret key, Judy will not be convinced: as far as Judy knows, Bob could be making it all up! In this paper we study Deniable Authentication in the setting where Judy can additionally obtain Alice’s secret key. Informally, we want that knowledge of Alice’s secret key does not help Judy in learning whether Alice sent any messages, even if Bob does not have Alice’s secret key and even if Bob cooperates with Judy by giving her his own secret key. This stronger flavor of Deniable Authentication was not considered before and is particularly relevant for Group Messaging as it gives users stronger deniability guarantees. Our main contribution is a scalable “ ” ( ) scheme—a technical formalization of Deniable Authentication that is particularly useful for secure messaging for its confidentiality guarantees—that provides this stronger deniability guarantee. At its core lie new $$\mathrm { M{\textrm{DVS}}}$$ (Multi-Designated Verifier Signature) and $$\text {PKEBC}$$ (Public Key Encryption for Broadcast) scheme constructions: our $$\mathrm { M{\textrm{DVS}}}$$ is not only secure with respect to the new deniability notions, but it is also the first to be tightly secure under standard assumptions; our $$\text {PKEBC}$$ —which is also of independent interest—is the first with ciphertext sizes and encryption and decryption times that grow only linearly in the number of receivers. This is a significant improvement upon the construction given by Maurer et al. (EUROCRYPT ’22), where ciphertext sizes and encryption and decryption times are quadratic in the number of receivers.
Siamese Interaction and Fine-Tuning Representation of Chinese Semantic Matching Algorithm Based on RoBERTa-wwm-ext

Semantic matching research is the cornerstone of research in the fields of natural language similarity measurement and sensor ontology matching (OM). In the existing Chinese semantic matching methods, there are some shortcomings, such as the single dimension of semantic expression, the insufficient expression of context semantic relations, and the insufficient interaction of semantic information between different sentences. This paper proposes a Chinese semantic matching algorithm based on RoBERTa-wwm-ext with Siamese interaction and fine-tuning representation (RSIFR). The RSIFR model initializes the model with RoBERTa-wwm-ext as a vector of text. Firstly, a Siamese structure with embedded soft alignment attention mechanism and BiLSTM is constructed to realize the information interaction between two sentences. Secondly, LSTM-BiLSTM network structure is constructed to enhance the expression of semantic logic before and after sentences. Then, build a training model with fine-tuning mechanism. Fine tune the text’s eigenvector parameters through label supervision. Finally, the fusion vectors of the sentence pairs are inserted into the MLP network layer, resulting in semantic matching results. RSIFR model starts from a variety of dimensions, strengthens the expression ability of vectors to text semantic relations, deeply mines the semantic similarities and differences between different sentences, and generally improves the Chinese semantic matching performance. Experiments on the public dataset LCQMC show that our model outperforms existing Chinese semantic matching models.
Application of big data classification effects based on neural network in video English course and relevant optimization suggestions

Due to the improvement of Internet technology and information technology, more and more students hope to learn and consolidate knowledge through video in the classroom. Teachers are more accustomed to using video in the classroom to improve and improve their teaching quality. In the current English class, teachers and students are more accustomed to using video English for teaching. English teaching videos are informative, intuitive and efficient. Through video teaching, we can make the classroom atmosphere more interesting, thus simplifying complex problems. In this context, this paper analyzes how neural networks can improve the application effect of English video courses in the context of big data, optimizes the PDCNO algorithm by using the neural network principle, and then discusses the impact of the optimized PDCNO algorithm on classification and system performance. This improves the accuracy of English video, reduces the execution time of the algorithm and reduces the memory occupation. Compared with ordinary video, the training time required under the same training parameters is shorter, and the convergence speed of the model itself will be faster. From the students' attitude towards video teaching, we can see that students prefer video English teaching, which also reflects the effectiveness of neural network big data in English video teaching. This paper introduces the neural network and big data technology into the video English course to improve the teaching effectiveness.