Reviewerly/exHarmony huggingface dataset:
One-Out-of-Many Unclonable Cryptography: Definitions, Constructions, and More

The no-cloning principle of quantum mechanics enables us to achieve amazing unclonable cryptographic primitives, which is impossible in classical cryptography. However, the security definitions for unclonable cryptography are tricky. Achieving desirable security notions for unclonability is a challenging task. In particular, there is no indistinguishable-secure unclonable encryption and quantum copy-protection for single-bit output point functions in the standard model. To tackle this problem, we introduce and study relaxed but meaningful security notions for unclonable cryptography in this work. We call the new security notion one-out-of-many unclonable security. We obtain the following results. Thus, we obtain one-out-of-many indistinguishable-secure unclonable encryption, one-out-of-many copy-protection for single-bit output point functions, and one-out-of-many unclonable PE in the standard model from the LWE assumption. In addition, our one-time SDE scheme is the first multi-bit SDE scheme that does not rely on any oracle heuristics and strong assumptions such as indistinguishability obfuscation and witness encryption.
Counting Unpredictable Bits: A Simple PRG from One-Way Functions

A central result in the theory of Cryptography, by Håstad, Imagliazzo, Luby and Levin [SICOMP’99], demonstrates that the existence one-way functions (OWF) implies the existence of pseudo-random generators (PRGs). Despite the fundamental importance of this result, and several elegant improvements/simplifications, analyses of constructions of PRGs from OWFs remain complex (both conceptually and technically). Our goal is to provide a construction of a PRG from OWFs with a simple proof of security; we thus focus on the setting of non-uniform security (i.e., we start off with a OWF secure against non-uniform PPT, and we aim to get a PRG secure against non-uniform PPT). Our main result is a construction of a PRG from OWFs with a self-contained, simple, proof of security, relying only on the Goldreich-Levin Theorem (and the Chernoff bound). Although our main goal is simplicity, the construction, and a variant there-of, also improves the efficiency—in terms of invocations and seed lengths—of the state-of-the-art constructions due to [Haitner-Reingold-Vadhan, STOC’10] and [Vadhan-Zheng, STOC’12], by a factor $$O(\log ^2 n)$$ . The key novelty in our analysis is a generalization of the Blum-Micali [FOCS’82] notion of unpredictabilty—rather than requiring that every bit in the output of a function is unpredictable, we count how many unpredictable bits a function has, and we show that any OWF on n input bits (after hashing the input and the output) has $$n+O(\log n)$$ unpredictable output bits. Such unpredictable bits can next be “extracted” into a pseudorandom string using standard techniques.
Reversible Data Hiding in Encrypted Images Based on Image Reprocessing and Polymorphic Compression

With the rapid development of cloud computing and privacy protection, Reversible Data Hiding in Encrypted Images (RDHEI) has attracted increasing attention, since it can achieve covert data transmission and lossless image recovery. To realize reversible data hiding with high embedding capacity, a new RDHEI method is proposed in this paper. First, we introduce the Image Reprocessing and Polymorphic Compression (IRPC) scheme, which can classify the images and then vacate enough room for embedding. After that, an improved RDHEI method combined with the IRPC scheme and a chaotic encryption algorithm is presented. In this method, the content owner uses the IRPC scheme to reserve embeddable rooms in the original image and then utilizes a six-dimensional chaotic encryption system to encrypt the reserved image into an encrypted image. After receiving the encrypted image, the data hider can embed additional data into it to obtain the marked encrypted image. According to the different keys the receiver has, the embedded data or the original image can be extracted or recovered from the marked encrypted image without error. Extensive experimental results show that the average Embedding Rate (ER) of our proposed method on the datasets BOSSbase, BOWS-2, and UCID is higher than that of the baseline method by 0.1bpp. At the same time, the security performance of the image is also improved.
Generalized Special-Sound Interactive Proofs and Their Knowledge Soundness

A classic result in the theory of interactive proofs shows that a special-sound $$\varSigma $$ -protocol is automatically a proof of knowledge. This result is very useful to have, since the latter property is typically tricky to prove from scratch, while the former is often easy to argue — if it is satisfied. While classic $$\varSigma $$ -protocols often are special-sound, this is unfortunately not the case for many recently proposed, highly efficient interactive proofs, at least not in this strict sense. Motivated by this, the original result was recently generalized to k-special-sound $$\varSigma $$ -protocols (for arbitrary, polynomially bounded k), and to multi-round versions thereof. This generalization is sufficient to analyze (e.g.) Bulletproofs-like protocols, but is still insufficient for many other examples. In this work, we push the relaxation of the special soundness property to the extreme, by allowing an arbitrary access structure $$\varGamma $$ to specify for which subsets of challenges it is possible to compute a witness, when given correct answers to these challenges (for a fixed first message). Concretely, for any access structure $$\varGamma $$ , we identify parameters $$t_\varGamma $$ and $$\kappa _\varGamma $$ , and we show that any $$\varGamma $$ -special-sound $$\varSigma $$ -protocol is a proof of knowledge with knowledge error $$\kappa _\varGamma $$ if $$t_\varGamma $$ is polynomially bounded. Similarly for multi-round protocols. We apply our general result to a couple of simple but important example protocols, where we obtain a tight knowledge error as an immediate corollary. Beyond these simple examples, we analyze the FRI protocol. Here, showing the general special soundness notion is non-trivial, but can be done (for a certain range of parameters) by recycling some of the techniques used to argue ordinary soundness of the protocol (as an IOP). Again as a corollary, we then derive that the FRI protocol, as an interactive proof by using a Merkle-tree commitment, has a knowledge extractor with almost optimal knowledge error, with the caveat that the extractor requires (expected) quasi-polynomial time. Finally, building up on the technique for the parallel repetition of k-special-sound $$\varSigma $$ -protocols, we show the same strong parallel repetition result for $$\varGamma $$ -special-sound $$\varSigma $$ -protocol and its multi-round variant.
Lower Bounds on Anonymous Whistleblowing

Anonymous transfer, recently introduced by Agrikola, Couteau and Maier [3] (TCC ’22), allows a sender to leak a message anonymously by participating in a public non-anonymous discussion in which everyone knows who said what. This opens up the intriguing possibility of using cryptography to ensure strong anonymity guarantees in a seemingly non-anonymous environment. The work of [3] presented a lower bound on anonymous transfer, ruling out constructions with strong anonymity guarantees (where the adversary’s advantage in identifying the sender is negligible) against arbitrary polynomial-time adversaries. They also provided a (heuristic) upper bound, giving a scheme with weak anonymity guarantees (the adversary’s advantage in identifying the sender is inverse in the number of rounds) against fine-grained adversaries whose run-time is bounded by some fixed polynomial that exceeds the run-time of the honest users. This leaves a large gap between the lower bound and the upper bound, raising the intriguing possibility that one may be able to achieve weak anonymity against arbitrary polynomial time adversaries, or strong anonymity a-gainst fine grained adversaries. In this work, we present improved lower bounds on anonymous transfer, that rule out both of the above possibilities: Consequently, constructions of anonymous transfer can only provide security against fine-grained adversaries, and even in that case they achieve at most weak quantitative forms of anonymity.
Anonymous Permutation Routing

The Non-Interactive Anonymous Router (NIAR) model was introduced by Shi and Wu [SW21] as an alternative to conventional solutions to the anonymous routing problem, in which a set of senders wish to send messages to a set of receivers. In contrast to most known approaches to support anonymous routing (e.g. mix-nets, DC-nets, etc.), which rely on a network of routers communicating with users via interactive protocols, the NIAR model assumes a single router and is inherently non-interactive (after an initial setup phase). In addition to being non-interactive, the NIAR model is compelling due to the security it provides: instead of relying on the honesty of some subset of the routers, the NIAR model requires anonymity even if the router (as well as an arbitrary subset of senders/receivers) is corrupted by an honest-but-curious adversary. In this paper, we present a protocol for the NIAR model that improves upon the results from [SW21] in two ways:
How to Compile Polynomial IOP into Simulation-Extractable SNARKs: A Modular Approach

Most succinct arguments (SNARKs) are initially only proven knowledge sound (KS). We show that the commonly employed compilation strategy from polynomial interactive oracle proofs (PIOP) via polynomial commitments to knowledge sound SNARKS actually also achieves other desirable properties: weak unique response (WUR) and trapdoorless zero-knowledge (TLZK); and that together they imply simulation extractability (SIM-EXT). The factoring of SIM-EXT into KS + WUR + TLZK is becoming a cornerstone of the analysis of non-malleable SNARK systems. We show how to prove WUR and TLZK for PIOP compiled SNARKs under mild falsifiable assumptions on the polynomial commitment scheme. This means that the analysis of knowledge soundness from PIOP properties that inherently relies on non-falsifiable or idealized assumption such as the algebraic group model (AGM) or generic group model (GGM) need not be repeated. While the proof of WUR requires only mild assumptions on the PIOP, TLZK is a different matter. As perfectly hiding polynomial commitments sometimes come at a substantial performance premium, SNARK designers prefer to employ deterministic commitments with some leakage. This results in the need for a stronger zero-knowledge property for the PIOP. The modularity of our approach implies that any analysis improvements, e.g. in terms of tightness, credibility of the knowledge assumption and model of the KS analysis, or the precision of capturing real-world optimizations for TLZK also benefits the SIM-EXT guarantees.
Holographic SNARGs for P and Batch-NP from (Polynomially Hard) Learning with Errors

A succinct non-interactive argument (SNARG) is called holographic if the verifier runs in time sub-linear in the input length when given oracle access to an encoding of the input. We present holographic SNARGs for P and Batch-NP under the learning with errors (LWE) assumption. Our holographic SNARG for P has a verifier that runs in time $$\textsf{poly}(\lambda , \log T, \log n)$$ for T-time computations and $$n$$ -bit inputs ( $$\lambda $$ is the security parameter), while our holographic SNARG for Batch-NP has a verifier that runs in time $$\textsf{poly}(\lambda , T, \log k)$$ for k instances of T-time computations. Before this work, constructions with the same asymptotic efficiency were known in the designated-verifier setting or under the sub-exponential hardness of the LWE assumption. We obtain our holographic SNARGs (in the public-verification setting under the polynomial hardness of the LWE assumption) by constructing holographic SNARGs for certain hash computations and then applying known/trivial transformations. As an application, we use our holographic SNARGs to weaken the assumption needed for a recent public-coin 3-round zero-knowledge (ZK) argument [Kiyoshima, CRYPTO 2022]. Specifically, we use our holographic SNARGs to show that a public-coin 3-round ZK argument exists under the same assumptions as the state-of-the-art private-coin 3-round ZK argument [Bitansky et al., STOC 2018].
Generic-Group Lower Bounds via Reductions Between Geometric-Search Problems: With and Without Preprocessing

The generic-group model ( $$ \textrm{GGM}$$ ) aims to capture algorithms working over groups of prime order that only rely on the group operation, but do not exploit any additional structure given by the concrete implementation of the group. In it, it is possible to prove information-theoretic lower bounds on the hardness of problems like the discrete logarithm (DL) or computational Diffie-Hellman (CDH). Thus, since its introduction, it has served as a valuable tool to assess the concrete security provided by cryptographic schemes based on such problems. A work on the related algebraic-group model (AGM) introduced a method, used by many subsequent works, to adapt $$ \textrm{GGM}$$ lower bounds for one problem to another, by means of conceptually simple reductions. In this work, we propose an alternative approach to extend $$ \textrm{GGM}$$ bounds from one problem to another. Following an idea by Yun [EC15], we show that, in the $$ \textrm{GGM}$$ , the security of a large class of problems can be reduced to that of geometric search-problems. By reducing the security of the resulting geometric-search problems to variants of the search-by-hypersurface problem, for which information theoretic lower bounds exist, we give alternative proofs of several results that used the AGM approach. The main advantage of our approach is that our reduction from geometric search-problems works, as well, for the $$\textrm{GGM}$$ with preprocessing (more precisely the bit-fixing $$ \textrm{GGM}$$ introduced by Coretti, Dodis and Guo [Crypto18]). As a consequence, this opens up the possibility of transferring preprocessing $$ \textrm{GGM}$$ bounds from one problem to another, also by means of simple reductions. Concretely, we prove novel preprocessing bounds on the hardness of the d-strong discrete logarithm, the d-strong Diffie-Hellman inversion, and multi-instance CDH problems, as well as a large class of Uber assumptions. Additionally, our approach applies to Shoup’s GGM without additional restrictions on the query behavior of the adversary, while the recent works of Zhang, Zhou, and Katz [AC22] and Zhandry [Crypto22] highlight that this is not the case for the AGM approach.
Privacy-Preserving Image Classification and Retrieval Scheme over Encrypted Images

Image retrieval is a crucial function in several emerging computer vision applications, including online medical diagnosis and image recognition systems. With an increasing number of images being generated and outsourced to public clouds, there is a growing concern about privacy leaks of image contents. To address this issue, we propose an efficient privacy-preserving image classification and retrieval scheme (PICR) that employs low-dimensional vectors to represent image categories and feature vectors, thereby improving retrieval efficiency and reducing index storage costs. First, we design a feature extraction model based on convolutional neural network (CNN) to generate segmented hash codes that represent both image categories and features. Next, the cryptographic hierarchical index structure based on the category hash code is designed to improve retrieval accuracy and efficiency. Then, we employ random vectors and the Learning With Errors (LWE)-based secure k-Nearest Neighbour (kNN) algorithm to preserve the privacy of segmented hash codes and file-access patterns. Finally, we provide the security analysis that verifies our PICR scheme can protect image privacy as well as indexing and query privacy. Experimental evaluation demonstrates that our proposed scheme outperforms the existing state-of-the-art schemes in terms of retrieval accuracy, search efficiency and storage costs.
Analisa dan Perancangan Sistem Informasi Sekolah Terintegrasi Media Sosial sebagai Media Promosi

In the era of the industrial revolution 5.0, many changes occurred in various fields one of the revolution is information system. The information system discussed this time refers to an agency's information system in schools. SMK PGRI 1 Bangkalan is one of the schools at the vocational secondary education level in Bangkalan Regency which does not yet have a website-based information system and has a total of no more than 50 students. A website-based information system can be a recommendation in overcoming these problems. This system can be used by the school to disseminate information about SMK which can be used as a promotional medium and will be integrated directly with social media. This study uses the waterfall model which is analogous to a waterfall. The waterfall model is used as a model reference in developing an information system. The results of this study are the design of a school information system that is integrated by social media account as a promotional medium in the form such as use case diagrams, flowcharts, database designs, and website interface designs.
Prediction Of Student Graduation Using The K-Nearest Neighbor Method Case Study in Politeknik Negeri Tanah Laut

Tanah Laut State Polytechnic as one of the universities in Indonesia has definitely paid attention to the quality of its students. One way is to predict student graduation. Graduation predictions can help study programs and academic supervisors review and pay special attention to students, especially students who are predicted to not graduate on time. Realizing one way to pay attention to the quality of students can be realized by creating a Student Graduation Prediction system using the Web-Based K-Nearest Neighbor (KNN) Method. The K-Nearest Neighbors method is an object classification method based on training data by finding the nearest neighbor value to determine the class of the new data. In the Student Graduation Prediction using the K-Nearest Neighbor Method, there is a section that can process training data, test data, the process of calculating student graduation predictions, and displaying the results obtained from the KNN calculation which has two classification classes, namely graduated and not passed. Based on the results of the study, it was found that KNN with different k values obtained different levels of accuracy, data testing with a value of k=1 obtained an accuracy rate of 83.33%, the value of k=2 obtained an accuracy rate of 79.17%, the value of k=3 to k= 8 obtained an accuracy rate of 95.83%, and the values of k=9 and k=10 obtained an accuracy rate of 91.67%. It can be concluded that the test with a value of k=3 to k=8 obtained the best or highest level of accuracy.
Perbandingan Algoritma Fisher-Yates Shuffle Dan Linear Congruent Method Pada Aplikasi Game Susun Ayat Al-Qur’an Berbasis Android

A problem that is often encountered among Qur’an memorized is the inability to memorize verses randomly. Therefore, a system is needed that is able to train the memorization of the Qur'an memorization so that it is able to memorize even with the position of the scrambled verses. To randomize verse chunks, a method is needed that can generate random numbers. Among the algorithms capable of generating random numbers are the Linear Congruent Method and the Fisher-Yates Shuffle. Of the two algorithms, no more effective algorithm has been found. For this reason, a comparison will be made by applying algorithms to Android-based game applications with the puzzle genre. This study aims to build an educational game application with the puzzle genre on the arrangement of quranic verses by comparing the effectiveness of the Linear Congruent Method and Fisher-Yates Shuffle algorithms in randomizing verses in games. The game is run in an Android application. Based on the tests that have been carried out, the results show that Linear Congruent Method has a pattern in generating random numbers while the Fisher-Yates Shuffle does not require it, so it can be concluded that the Fisher-Yates Shuffle algorithm is the most effective in randomizing.
Three Party Secure Computation with Friends and Foes

In secure multiparty computation (MPC), the goal is to allow a set of mutually distrustful parties to compute some function of their private inputs in a way that preserves security properties, even in the face of adversarial behavior by some of the parties. However, classical security definitions do not pose any privacy restrictions on the view of honest parties. Thus, if an attacker adversarially leaks private information to honest parties, it does not count as a violation of privacy. This is arguably undesirable, and in real-life scenarios, it is hard to imagine that possible users would agree to have their private information revealed, even if only to other honest parties. To address this issue, Alon et al. [CRYPTO 20] introduced the notion of security with friends and foes (FaF security). In essence, (t, h)-FaF security requires that a malicious adversary corrupting up to t parties cannot help a coalition of h semi-honest parties to learn anything beyond what they can learn from their inputs and outputs (combined with the input and outputs of the malicious parties). They further showed that (t, h)-FaF security with n parties is achievable for any functionality if $$2t+h<n$$ , and for some functionality, (t, h)-FaF security is impossible assuming $$2t+h\ge n$$ . A remaining important open problem is to characterize the set of n-party functionalities that can be computed with (t, h)-FaF security assuming $$2t+h\ge n$$ . In this paper, we focus on the special, yet already challenging, case of (1, 1)-FaF security for three-party, 2-ary (two inputs), symmetric (all parties output the same value) functionalities. We provide several positive results, a lower bound on the round complexity, and an impossibility result. In particular, we prove the following. (1) we identify a large class of three-party Boolean symmetric 2-ary functionalities that can be computed with (1, 1)-FaF full security, and (2) We identify a large class of three-party (possibly non-Boolean) symmetric 2-ary functionalities, for which no $$O(\log \kappa )$$ -round protocol computes them with (1, 1)-FaF full security. This matches the round complexity of our positive results for various interesting functionalities, such as equality of strings.
Broadcast-Optimal Four-Round MPC in the Plain Model

The prior works of Cohen, Garay and Zikas (Eurocrypt 2020), Damgård, Magri, Ravi, Siniscalchi and Yakoubov (Crypto 2021) and Damgård, Ravi, Siniscalchi and Yakoubov (Eurocrypt 2023) study 2-round Multi-Party Computation (where some form of set-up is required). Motivated by the fact that broadcast is an expensive resource, they focus on so-called broadcast optimal MPC, i.e., they give tight characterizations of which security guarantees are achievable, if broadcast is available in the first round, the second round, both rounds, or not at all. This work considers the natural question of characterizing broadcast optimal MPC in the plain model where no set-up is assumed. We focus on 4-round protocols, since 4 is known to be the minimal number of rounds required to securely realize any functionality with black-box simulation. We give a complete characterization of which security guarantees, (namely selective abort, selective identifiable abort, unanimous abort and identifiable abort) are feasible or not, depending on the exact selection of rounds in which broadcast is available.