The ongoing challenge in the world of blockchain technology is finding a solution to the trilemma that involves balancing decentralization, security, and scalability. This paper introduces a pioneering blockchain architecture designed to transcend this trilemma, uniting advanced cryptographic methods, inventive security protocols, and dynamic decentralization mechanisms. Employing established techniques such as elliptic curve cryptography, Schnorr verifiable random function, and zero‐knowledge proof (zk‐SNARK), alongside groundbreaking methodologies for stake distribution, anomaly detection, and incentive alignment, our framework sets a new benchmark for secure, scalable, and decentralized blockchain ecosystems. The proposed system surpasses top‐tier consensuses by attaining a throughput of 1700+ transactions per second, ensuring robust security against all well‐known blockchain attacks without compromising scalability and demonstrating solid decentralization in benchmark analysis alongside 25 other blockchain systems, all achieved with an affordable hardware cost for validators and an average CPU usage of only 16.1%.
Radio Frequency Identification (RFID) promotes the fundamental tracking procedure of the Internet of Things (IoT) network due to its autonomous data collection as well as transfer incurring low costs. To overcome the insecure exchange of tracking data and to prevent unauthorized access, parallel dependency RFID grouping-proof protocol is applied by the reader to authenticate tags simultaneously. However, conventional grouping-proof authentication schemes are not sufficient for the memory constraint RFID tags due to the recurrent utilization of a 128-bit PRNG (Pseudo Random Number Generator) function. Alternatively, the existing parallel-dependency grouping-proof schemes are not able to overcome numerous limitations regarding session establishment, efficient key management, and multicast message communication within the specified group. In this research, a lightweight, secure, and efficient communication protocol is proposed to overcome the aforementioned limitations using Elliptic Curve Cryptography (ECC) and Zero-Knowledge property to establish a session key among the participated tags, reader, and remote server. The proposed scheme can work in offline mode. The proposed ECC-based parallel dependency grouping-proof scheme is referred to as ECC-PDGPP which abides by the rules of the EPC class-1 gen-2 (C1 G2) standard of RFID tags. Finally, the proposed protocol is analyzed using a formal random oracle model and simulated using a well-known AVISPA simulation tool that shows the proposed scheme is well protected against all potential security threats.
Zero-knowledge range proofs (ZKRPs) allow a prover to convince a verifier that a secret value lies in a given interval. ZKRPs have numerous applications: from anonymous credentials and auctions, to confidential transactions in cryptocurrencies. At the same time, a plethora of ZKRP constructions exist in the literature, each with its own trade-offs. In this work, we systematize the knowledge around ZKRPs. We create a classification of existing constructions based on the underlying building techniques, and we summarize their properties. We provide comparisons between schemes both in terms of properties as well as efficiency levels, and construct a guideline to assist in the selection of an appropriate ZKRP for different application requirements. Finally, we discuss a number of interesting open research problems.
Javier José Díaz Rivera, Muhammad Afaq, Wang‐Cheol Song
As network systems advance and become more sophisticated, the associated security challenges grow more complex. The zero trust model emerges as a new paradigm to address this, significantly emphasizing robust and continuous identity verification. Multi-factor authentication (MFA) methods have become crucial for enhancing authentication security within this framework. Additionally, the integration of blockchain technology is increasingly recognized for its potential to strengthen identity trustworthiness further, complementing the zero trust approach by providing a more secure and transparent identity verification process. However, privacy concerns remain, especially in public blockchain environments where personal data is vulnerable to inadvertent exposure. Also, using centralized servers for authentication, even in systems integrated with blockchain, presents the risk of creating single points of failure. This paper introduces a privacy-preserving MFA system that harnesses the decentralized capabilities of blockchain technology to enable a Distributed Authentication Mechanism (DAM) as a network of authenticators for enhancing the reliability of the authentication process. This system utilizes blockchain-based Zero-Knowledge Proofs (ZKP) as a privacy mechanism to prove the knowledge of a One-Time Password (OTP). This approach not only ensures the authenticity of the proof authenticity but also confirms the identity of the prover. In the final stage of the MFA process, non-transferable, non-fungible tokens (NFTs) are employed as authentication tokens for identity verification. Our experimental results and comparative security analyses suggest a relevant contribution to secure, private, and dependable MFA framework research.
Privacy and security in the current modern, digital communication and data transfer-oriented world has become imperative. Most commonly used encryption methods often involve exposing sensitive information, which might be an open gate for potential vulnerabilities. This paper aims to explore the topic of applying ZKPs in cybersecurity in a comprehensive manner. For this purpose, Proposed work will provide an exhaustive description of the basic concepts of Zero-Knowledge Proofs , which refer to both the interactive and non-interactive forms of the product. Additionally, the study will focus on presenting various cryptographic protocols and algorithms utilizing Zero-Knowledge Proofs , such as zk-SNARKs and zk-STARKs . In addition to theoretical studies, Proposed work analyze the practical implementation details of Zero-Knowledge Proofs implementations , cryptographic libraries, programming languages, and frameworks commonly used to create ZKP-based applications . Zero-knowledge proofs enable groundbreaking approaches to address cybersecurity problems with an emphasis on user privacy and data confidentiality. On average, cryptographic operations experienced delays of approximately 10 milliseconds which was not intrusive for real-time systems. The system’s throughout remained at a steady average of 100 Mbps all times, so it performed well at processing data despite cryptographic overhead. The packet delivery ratio was constantly high at 98%, implying that most data packets were delivered consistently even over encrypted communication paths.
Autonomous decision-making in decentralized multi-agent systems (MAS) poses significant challenges related to security, scalability, and privacy. This paper introduces an innovative architecture that integrates Decentralized Identifiers (DIDs), Zero-Knowledge Proofs (ZKPs), Hyperledger Fabric blockchain, OAuth 2.0 authorization, and the Command Query Responsibility Segregation (CQRS) pattern to establish a secure, scalable, and privacy-focused framework for MAS. The use of DIDs and ZKPs ensures secure, self-sovereign identities and enables privacy-preserving interactions among autonomous agents. Hyperledger Fabric provides an immutable ledger, ensuring data integrity and facilitating transparent transaction processing through smart contracts. The CQRS pattern, combined with event sourcing, optimizes the system’s ability to handle high volumes of read and write operations, enhancing performance and scalability. Practical applications are showcased in Smart Grids, Healthcare Data Management, Secure Internet of Things (IoT) Networks, and Supply Chain Management, highlighting the architecture’s ability to address industry-specific challenges. This integration offers a robust solution for ensuring trust, verifiability, and scalability in distributed systems while preserving the confidentiality of agents.
Zero-knowledge proof (ZKP) systems have surged attention and held a fundamental role in contemporary cryptography. Zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) protocols dominate the ZKP usage, implemented through arithmetic circuit programming paradigm. However, underconstrained or overconstrained circuits may lead to bugs. The former refers to circuits that lack the necessary constraints, resulting in unexpected solutions and causing the verifier to accept a bogus witness, and the latter refers to circuits that are constrained excessively, resulting in lacking necessary solutions and causing the verifier to accept no witness. This article introduces a novel approach for pinpointing two distinct types of bugs in ZKP circuits. The method involves encoding the arithmetic circuit constraints to polynomial equation systems and solving them over finite fields by the computer algebra system . The classification of verification results is refined, greatly enhancing the expressive power of the system. A tool, AC 4 , is proposed to represent the implementation of the method. Experiments show that AC 4 demonstrates an increase in the solved rate, showing a 36.7% improvement over Picus and CIVER, and a slight improvement over halo2-analyzer, a checker for halo2 circuits. Within a solvable range, the checking time has also exhibited noticeable improvement, demonstrating a magnitude increase compared to previous efforts.
Kuznetsov, Oleksandr, Anton Yezhov, Vladyslav Yusiuk, Alexandr Kuznetsov
Zero-knowledge proofs (ZKPs) have emerged as a promising solution to address the scalability challenges in modern blockchain systems. This study proposes a methodology for generating and verifying ZKPs to ensure the computational integrity of cryptographic hashing, specifically focusing on the SHA-256 algorithm. By leveraging the Plonky2 framework, which implements the PLONK protocol with the FRI commitment scheme, we demonstrate the efficiency and scalability of our approach for both random data and real data blocks from the NEAR blockchain. The experimental results show consistent performance across different data sizes and types, with the time required for proof generation and verification remaining within acceptable limits. The generated circuits and proofs maintain manageable sizes, even for real-world data blocks with a large number of transactions. The proposed methodology contributes to the development of secure and trustworthy blockchain systems, where the integrity of computations can be verified without revealing the underlying data. Further research is needed to assess the applicability of the approach to other cryptographic primitives and to evaluate its performance in more complex real-world scenarios.
Open access
3 source records
Cryptography and Data Security
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Camilla Fioravanti, Christoforos N. Hadjicostis, Gabriele Oliva
Networked Control Systems (NCS) are pivotal for sectors like industrial automation, autonomous vehicles, and smart grids. However, merging communication networks with control loops brings complexities and security vulnerabilities, necessitating strong protection and authentication measures. This paper introduces an innovative Zero-Knowledge Proof (ZKP) scheme tailored for NCSs, enabling a networked controller to prove its knowledge of the dynamical model and its ability to control a discrete-time linear time-invariant (LTI) system to a sensor, without revealing the model. This verification is done through the controller's capacity to produce suitable control signals in response to the sensor's output demands. The completeness, soundness, and zero-knowledge properties of the proposed approach are demonstrated. The scheme is subsequently extended by considering the presence of delays and output noise. Additionally, a dual scenario where the sensor proves its model knowledge to the controller is explored, enhancing the method's versatility. Effectiveness is shown through numerical simulations and a case study on distributed agreement in multi-agent systems.
Aušrys Kilčiauskas, Antanas Bendoraitis, Eligijus Sakalauskas
One of the main trends for the monitoring and control of business processes is to implement these processes via private blockchain systems. These systems must ensure data privacy and verifiability for the entire network here denoted by ‘Net’. In addition, every business activity should be declared to a trusted third party (TTP), such as an Audit Authority (AA), for tax declaration and collection purposes. We present a solution for a confidential and verifiable realization of transactions based on the Unspent Transaction Output (UTxO) paradigm. This means that the total sum of transaction inputs (incomes) $In$ must be equal to the total sum of transaction outputs (expenses) $Ex$, satisfying the balance equation $In=Ex$. Privacy in a private blockchain must be achieved through the encryption of actual transaction values. However, it is crucial that all participants in the network be able to verify the validity of the transaction balance equation. This poses a challenge with probabilistically encrypted data. Moreover, the inputs and outputs are encrypted with different public keys. With the introduction of the AA, the number of different public keys for encryption can be reduced to two. Incomes are encrypted with the Receiver’s public key and expenses with the AA’s public key. The novelty of our realization lies in taking additively-multiplicative, homomorphic ElGamal encryption and integrating it with a proposed paradigm of modified Schnorr identification providing a non-interactive zero-knowledge proof (NIZKP) using a cryptographically secure h-function. Introducing the AA as a structural element in a blockchain system based on the UTxO enables effective verification of encrypted transaction data for the Net. This is possible because the proposed NIZKP is able to prove the equivalency of two ciphertexts encrypted with two different public keys and different actors. This integration allows all users on the Net to check the UTxO-based transaction balance equation on encrypted data. The security considerations of the proposed solution are presented.
AI and zero-knowledge proofs (ZKPs) may revolutionize cryptographic protocol privacy, as this research shows. The report examines how AI may improve ZKP efficiency, scalability, and security and identifies developing AI-driven privacy-preserving technologies across sectors. The study reviews secondary data from peer-reviewed journals, technical reports, and conference proceedings. Key results show that AI automates proof creation, optimizes verification procedures, and identifies weaknesses, allowing innovative architectures like federated learning mixed with ZKPs for safe, collaborative AI training. The research shows AI's potential to improve privacy in banking, healthcare, and secure identity management. However, concerns about the computational needs of the AI model, explainable systems, and interoperability persist. The policy implications highlight standardization, security framework improvements, and research to solve these shortcomings. The policy should also support openness and accountability in AI-driven cryptography systems to build confidence and acceptance. This paper shows how AI might transform privacy-preserving cryptographic methods and how to overcome their existing limitations to maximize their promise.