Igor A. Kalmykov, Владимир Копытов, A A Olenev, Daniil Vyacheslavovich Dukhovnyj · 6 authors
The use of a satellite Internet systems (SIS) makes it possible to effectively support technologies such as the Industrial Internet of Things (IIoT). This technology is especially relevant for oil and gas industry enterprises implementing the development of deposits located on the shelf of the Arctic Ocean. As the number of countries and companies engaged in the development of deposits in the Arctic Ocean increases, the number of groupings of low-orbit satellites increases as well. This can lead to a situation when an intruder satellite intercepts a control command and then imposes it on a receiver located on an unattended object. It is possible to reduce the effectiveness of such relay spoofing interference by using the satellite authentication protocol. The conducted studies have shown that authentication protocols with zero-knowledge proof have high cryptographic resistance to a satellite response being correctly picked up. However, they have a drawback. It is a significant time spent on determining the status of the satellite, which is caused by the fact that calculations are performed using a large module (128 or more digits). This disadvantage can be eliminated by using modular residue classes codes (MRCC).
Due to an increase in agricultural mislabeling and carelesshandling of non-perishable foods in recent years, consumers have been calling for the food sector to be more transparent. Due to information dispersion between divisions and the propensity to record inaccurate data, current traceability solutions typically fail to provide reliable farm-to-fork histories ofproducts. The three most enticing characteristics of blockchain technology areopenness, integrity, and traceability, which make it a potentially crucial tool for guaranteeing the integrity and correctness of data. In this paper, we suggest a permissioned blockchain system run by organizations, such as regulatory bodies, to promote the origin-tracking of shelf-stable agricultural products. We propose a four-tiered architecture, parallel side chains, Zero-Knowledge Proofs (ZKPs), and Interplanetary File Systems (IPFS). These ensure that information about where an item came from is shared, those commercial competitors cannot get to it, those big storage problems are handled, and the system can be scaled to handle many transactions at once. Thesolution maintains the confidentiality of all transaction flows whenprovenance data is queried utilizing smart contracts and a consumer-grade reliance rate. Extensive simulation testing using Ethereum Rinkeby and Polygon demonstrates reduced execution time, latency, and throughput overheads.
In the big data era, machine learning has devel-oped prominently and is widely used in real-world systems. Yet, machine learning raises fairness concerns, which incurs discrimination against groups determined by sensitive attributes such as gender and race. Many researchers have focused on developing fairness audit technique of machine learning model that enable users to protect themselves from discrimination. Existing solutions, however, rely on additional external trust as-sumptions, either on third-party entities or external components, that significantly lower the security. In this study, we propose a trustless verifiable fairness audit framework that assesses the fairness of ML algorithms while addressing potential security issues such as data privacy, model secrecy, and trustworthiness. With succinctness and non-interactive of zero knowledge proof, our framework not only guarantees audit integrity, but also clearly enhance security, enabling fair ML models to be publicly auditable and any client to verify audit results without extra trust assumption. Our evaluation on various machine learning models and real-world datasets shows that our framework achieves practical performance.
We construct the first actively-secure threshold version of the cryptosystem based on class groups from the so-called CL framework (Castagnos and Laguillaumie, 2015). We show how to use our threshold scheme to achieve general universally composable (UC) secure multiparty computation (MPC) with only transparent set-up, i.e., with no secret trapdoors involved. On the way to our goal, we design new zero-knowledge (ZK) protocols with constant communication complexity for proving multiplicative relations between encrypted values. This allows us to use the ZK proofs to achieve MPC with active security with only a constant factor overhead. Finally, we adapt our protocol for the so called “You-Only-Speak-Once” (YOSO) setting, which is a very promising recent approach for performing MPC over a blockchain. This is possible because our key generation protocol is simpler and requires significantly less interaction compared to previous approaches: in particular, our new key generation protocol allows the adversary to bias the public key, but we show that this has no impact on the security of the resulting cryptosystem.
Alex Ozdemir, Riad S. Wahby, Fraser Brown, Clark Barrett
Abstract Zero Knowledge Proofs (ZKPs) are cryptographic protocols by which a prover convinces a verifier of the truth of a statement without revealing any other information. Typically, statements are expressed in a high-level language and then compiled to a low-level representation on which the ZKP operates. Thus, a bug in a ZKP compiler can compromise the statement that the ZK proof is supposed to establish. This paper takes a step towards ZKP compiler correctness by partially verifying a field-blasting compiler pass, a pass that translates Boolean and bit-vector logic into equivalent operations in a finite field. First, we define correctness for field-blasters and ZKP compilers more generally. Next, we describe the specific field-blaster using a set of encoding rules and define verification conditions for individual rules. Finally, we connect the rules and the correctness definition by showing that if our verification conditions hold, the field-blaster is correct. We have implemented our approach in the CirC ZKP compiler and have proved bounded versions of the corresponding verification conditions. We show that our partially verified field-blaster does not hurt the performance of the compiler or its output; we also report on four bugs uncovered during verification.
Decentralized identities return control of identities to the identity owners. Although current work enhances the privacy of these publicly stored identities using encryption and zero-knowledge proofs, decentralized identities can still be abused due to the following problems: identity holders, e.g., blockchain peers, can profile identity owners by looking at “who is reading which identity data”, and identity verifiers, e.g., applications and websites, learn private data about owners, like their monetary values and previous transactions during the identity linking. In the worst case scenario, the identity holders and verifiers collaboratively profile users to learn more information. As a practical solution, we introduce the notion of Double Blind Proofs of Existence (DBPoE), which shows that an opened DID is committed in one of the constant-sized multi-generator Pedersen commitments (33 Bytes at 128-bit security), and nothing else. Hence, our DBPoE double-blinds identity holders and identity verifiers to mitigate private information leakage. Equally importantly, our multi-generator commitment-based DBPoE is more resistant to graph analysis than other one-of-many proofs, e.g., ring signatures, which we show mathematically using the maximal flow problem. Our DBPoE protocol has a size complexity ofO(log2(N) +m) when the real commitment is hidden inNcommitments andmgenerators are used, e.g., whenm= 4, a DBPoE of 1000 commitments is only 3 KB.
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.
In the era of digital markets, the challenge for consumers is discerning quality amidst information asymmetry . While traditional markets use brand mechanisms to address this issue, transferring such systems to internet-based P2P markets – where misleading practices like fake ratings are rampant – remains challenging. Current internet platforms strive to counter this through verification algorithms, but these efforts find themselves in a continuous tug-of-war with counterfeit actions. Exploiting the transparency, immutability, and traceability of blockchain technology, this paper introduces a robust reputation voting system grounded in it. Unlike existing blockchain-based reputation systems, our model harnesses an intrinsically economically incentivized approach to bolster agent integrity. We optimize this model to mirror real-world user behavior , preserving the reputation system’s foundational sustainability . Through Monte-Carlo simulations, using both uniform and power-law distributions enabled by an innovative inverse transform method, we traverse a broad parameter landscape, replicating real-world complexity. The findings underscore the promise of a sustainable, transparent, and formidable reputation mechanism. Given its structure, our framework can potentially function as a universal, sustainable oracle for offchain-onchain bridging, aiding entities in perpetually cultivating their reputation. Future integration with technologies like Ring Signature and Zero Knowledge Proof could amplify the system’s privacy facets, rendering it particularly influential in the ever-evolving digital domain.
Business process collaboration between independent parties is challenging when participants do not completely trust each other. Tracking actions and enforcing the activity authorizations of participants via blockchain-hosted smart contracts is an emerging solution to this lack of trust, with most state-of-the-art approaches generating the orchestrating smart contract logic from Business Process Model and Notation (BPMN) models. However, compared to centralized business process orchestration services, smart contract state typically leaks potentially sensitive information about the state of the collaboration, limiting the applicability of decentralized process orchestration. This paper presents a novel, collaboration confidentiality-preserving approach where the process orchestrator smart contract only stores encrypted and hashed process states and validates participant actions against a BPMN model using zero-knowledge proofs. We cover a subset of BPMN, which is sufficient from the practical point of view, support messagepassing between participants, and provide an open-source, endto-end prototype implementation that automatically generates the key software artifacts.
Reviews and reputation scores of sellers play an important role in decision-making process of potential buyers in an e-commerce system. A trustworthy and reliable reputation system is a crucial component in the e-commerce ecosystem, as buyers rely on it to make informed decisions. In this work, we propose a privacy-preserving decentralized reputation system designed to include countermeasures against some known attacks. Our model is built on two permissioned blockchains, namely Hyperledger Indy and Hyperledger Fabric. Hyperledger Indy provides an infrastructure for implementing verifiable credentials with Zero Knowledge Proof support, which is essential for privacy preservation, while Hyperledger Fabric is a robust platform for implementing smart contracts. One of the key advantages of the proposed approach is the use of verifiable credentials for digital identities of sellers, feedback tokens issued to buyers after performing an e-commerce transaction and discount tokens issued to buyers after feedback submission. This helps to ensure that the feedback and identity information is authentic and tamper-proof, reducing the likelihood of identity-related attacks. Additionally, the collection of feedbacks and application of business rules are implemented as smart contracts on Hyperledger Fabric blockchain. This provides a secure and transparent mechanism for processing feedback, reducing the likelihood of unfair feedbacks. Overall, the proposed approach presents a robust reputation system that can help reduce identity-related attacks and unfair feedbacks. The privacy-preserving nature of the system ensures that sensitive information is protected while still enabling the verification of digital identities. The use of feedback and discount tokens incentivizes buyers to provide accurate and honest feedback, which can help reduce unfair feedbacks and identity-related attacks. Finally, the use of smart contracts ensures transparency and immutability, which enhances the overall reliability of the system.
Alex Ozdemir, Gereon Kremer, Cesare Tinelli, Clark Barrett
Abstract We study satisfiability modulo the theory of finite fields and give a decision procedure for this theory. We implement our procedure for prime fields inside the cvc5 SMT solver. Using this theory, we construct SMT queries that encode translation validation for various zero knowledge proof compilers applied to Boolean computations. We evaluate our procedure on these benchmarks. Our experiments show that our implementation is superior to previous approaches (which encode field arithmetic using integers or bit-vectors).
Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is becoming more and more sophisticated and widely used in various fields such as social, tourism, industry and economy. However, the high level of interaction with the real world also means a huge risk of privacy leakage both for individuals and enterprises, which has hindered the wide deployment of metaverse. Then, it is inevitable to apply privacy computing techniques in the framework of metaverse, which is a current research hotspot. In this paper, we conduct comprehensive research on the necessity, taxonomy and challenges when privacy computing meets metaverse. Specifically, we first introduce the underlying technologies and various applications of metaverse, on which we analyze the challenges of data usage in metaverse, especially data privacy. Next, we review and summarize state-of-the-art solutions based on federated learning, differential privacy, homomorphic encryption, and zero-knowledge proofs for different privacy problems in metaverse. Finally, we show the current security and privacy challenges in the development of metaverse and provide open directions for building a well-established privacy-preserving metaverse system. For easy access and reference, we integrate the related publications and their codes into a GitHub repository: https://github.com/6lyc/Awesome-Privacy-Computing-in-Metaverse.git.
The paper discusses the basic principles of construction and the main types of zeroknowledge succinct non-interactive argument of knowledge (zk-SNARK) which is used in the model of a three-way insecure computing environment and based on sets of polynomials. A number of zk-SNARK cryptographic protocols with different algorithms for generating public parameters (Trusted Setup) are given, constructing succinct proofs of reliability calculations (Prover) and public/designated verification of proofs (Verifier). The cases of satisfying the feasibility of discrete functions (arithmetic/ Boolean circuits) using different polynomial sets are presented in quadratic arithmetic programs (QAP), square arithmetic programs (SAP), quadratic span programs (QSP), square span programs (SSP), quadratic polynomial programs (QPP), etc., also the use of authenticated data are described. The cryptographic transformations needed to build zk-SNARKs based on symmetric and asymmetric hash functions, exponential knowledge problems, digital signatures, homomorphic encryption, bilinear pairings based on elliptic curves, etc. are presented. Examples of multilateral verifiable calculations based on zk-SNARK are given.