Yash Bobde, Gokuleshwaran Narayanan, Manas Jati, S. P. Raja · 6 authors
In the rapidly evolving landscape of industrial ecosystems, Industrial IoT networks face increasing security challenges. Traditional security methods often struggle to protect these networks adequately, posing risks to data integrity, confidentiality, and access control. Our research introduces a methodology that leverages blockchain technology to enhance the security and trustworthiness of IoT networks. This approach starts with sensor nodes collecting and compressing data, followed by encryption using the ChaCha20-Poly1305 algorithm and transmission to local aggregators. A crucial element of our system is the private blockchain gateway, which processes and classifies data based on confidentiality levels, determining their storage in cloud servers or the Interplanetary File System for enhanced security. The system’s integrity and authenticity are further reinforced through the proof of authority consensus mechanism. This system employs Zero Knowledge Proof challenges for device authorization, optimizing data retrieval while maintaining a delicate balance between security and accessibility. Our methodology contributes to mitigating vulnerabilities in Industrial IoT networks and is part of a broader effort to advance the security and operational efficiency of these systems. It reflects an understanding of the diverse and evolving challenges in IoT security, emphasizing the need for continuous innovation and adaptation in this dynamic field.
Tácito Augusto Farias Júnior, Rafael Oliveira Vasconcelos, Admilson de Ribamar Lima Ribeiro
Privacy protection ensures that individuals have control over personal data, preventing abuse and preserving trust in the use of online services. In the “Digital Era”, where the collection, storage and processing of personal information have become ubiquitous, data privacy emerges as a relevant topic. In this sense, laws were created, such as the General Data Protection Law (LGPD) in Brazil and the General Data Protection Regulation (GDPR) in Europe, to control privacy and the processing of personal data. The article presents a comparative analysis of 2 (two) data privacy mechanisms, the Zero-Knowledge Proof (ZKP) and Ring Signatures, used in Blockchain, aiming at the legal and regulatory implications with the LGPD and GDPR. The comparative study between ZKP and Ring Signatures highlights the flexibility of ZKP in various contexts, including voting and secure authentication systems, while Ring Signatures offer significant advantages in terms of scalability and efficiency in systems where subscriber anonymity is considered fundamental. Furthermore, the legal and regulatory implications of the ZKP are discussed, mainly in relation to LGPD and GDPR. Finally, the article concludes that the comparative analysis offers insights into applications, challenges and legal and regulatory implications, particularly in relation to data privacy and compliance with regulations such as LGPD and GDPR.
Abstract In the evolving landscape of global education, the significance of inclusivity and equity has never been more important. Emphasizing the United Nation Sustainable Development Goal 4, this paper explores the innovative application of blockchain-powered Zero-Knowledge Proofs (ZKPs) technology in education, with a particular focus on disability inclusion. This study introduces a novel disability management system powered by Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK). This advanced system enables educational institutions to verify the status of students with disabilities without compromising their personal information, thereby preserving their privacy and reinforcing their identity. This paper evaluates the potential operational efficiency of this prototype system against the existing costs incurred by higher education institutions in disability schemes. It also examines the system’s potential to enhance self-disclosure among students with disability, which is pivotal for their academic success. By advocating for privacy and inclusivity, this study highlights the transformative potential of ZKP in creating an educational environment where students with disabilities can comfortably disclose their needs. This approach not only protects their confidentiality but also empowers them academically, aligning with the global commitment to accessible and inclusive education.
Cryptography has always been the science of Secure Communication. The past decade has been epitomized by the emergence of Blockchain Technology, without leaving Cryptography unaffected. The manifesto of Blockchains is Decentralization, making it inevitable that the information is stored and verified in real-time by thousands of participants. This spotlighted two necessities: information should be as concise as possible and verification of processes should be fast. From a cryptographic perspective, this translates to a central desideratum: Succinctness. A cryptographic construction is called Succinct if its algorithm is generating outputs that are (exponentially) smaller than the inputs. This allows the cryptosystem to treat large data and produce concise outputs that, nevertheless, preserve the desired functionality of the system. In this thesis, we are concerned with a specific type of Succinct cryptographic primitives: Succinct Commitments. Cryptographic commitments are objects that allow one to commit to some data, providing a binding representative. Then at any later point they can open back the (committed) data providing an opening proof, but without being able to open differently the representative. In more detail, in our work we deal with commitments with more fine-grained openings, where one can generate an opening proof of the commitment to a function f (m) of the initial data m. Firstly, we deal with set commitments with private (non-)memberhsip openings. We construct succinct zero-knowledge proofs for the problem of set (non-)membership. Intuitively, a zero- knowledge proof is a cryptographic primitive that allows one to prove a statement, in a sound way, without leaking any other information except for the fact that the statement holds. In a zero-knowledge proof for set membership first one commits to a public set and then a party can prove membership to the set but without betraying which element of the set exactly is. Such (set) commitments with this type of fine-grained openings are the cornerstone of Anonymous Cryptocurrencies such as Zcash. In particular we provide efficient zero-knowledge proofs for the opening of RSA accumulators, one of the most popular set commitments. First, we show efficient protocols for membership and non-membership of a single element. Then we construct succinct zero-knowledge membership proofs for multiple elements, where the size of the proof is independent of the number of elements proven. The two techniques are qualitatively different. Secondly, we switch our attention to Vector Commitments, with local positional openings. We put forth the notion of Incremental Aggregation, in which one can arbitrarily aggregate opening proofs of any positions into a single (concise) proof and inversely disaggregate a proof of multiple points to many. We show applications of this notion (1) to speeding up the proof computation by using precomputation and moderate-sized precomputed values and (2) to Verifiable Decentralized Storage. Finally, we provide efficient construction of Incrementally Aggregatable Vector Commitments from Groups of Unknown Order. Thirdly, we turn to Functional Commitments, for linear functions, where one commits to a vector v and then can open f(v) = y, for a public f. We construct functional commitments that admit constant-sized public parameters and proofs. To this end, our core technique is a novel succinct protocol of cardinality for a set committed with an RSA accumulator, which is in turn based on a Range Proof. Finally, we show a generic way to turn any Vector Commitment into a Key-Value Map Commitment for arbitrary keys. A Key-Value Map resembles a Vector but the ordering of the values is not characterized by subsequent indices but by arbitrary keys. Key-Value Maps are the core data-structures in Cryptocurrencies like Ethereum. Our construction of Key-Value Map Commitments is generic and is based on a novel cryptographic application of Cuckoo-Hashing. RESUMEN La última década se ha caracterizado por la aparición de la tecnología Blockchain, afectando la criptografía. El manifiesto de Blockchains es la Descentralización, en la que la información es guardada y verificada en tiempo real por miles de participantes. Esto centra la atención en dos necesidades: la información debe ser lo más concisa posible y la verificación de los procesos debe ser rápida. Desde una perspectiva criptográfica, esto se traduce en un desiderátum central: la Compacidad. En esta tesis, nos ocupamos de un tipo específico de primitivas criptográficas compactas: Compromisos Compactos. Los compromisos criptográficos son objetos que permiten comprom- eterse con algunos datos, proporcionando un representante vinculante, de modo que en cualquier momento posterior se pueden volver a abrir, proporcionando una prueba de apertura. En nuestro trabajo tratamos compromisos con aperturas más detalladas, donde se puede generar una prueba de apertura del compromiso con una función f (m) de los datos iniciales m. En primer lugar, nos ocupamos de compromisos de conjuntos con aperturas privadas de (no) pertenencia. Construimos pruebas compactas de conocimiento cero para el problema de la (no) pertenencia a conjuntos. Una prueba de conocimiento cero es una primitiva criptográfica que permite probar una afirmación, de forma sólida, sin filtrar ninguna otra información excepto el hecho de que la afirmación es cierta. En una prueba de conocimiento cero para la pertenencia a un conjunto, primero uno se compromete con un conjunto público y luego una parte puede demostrar la pertenencia al conjunto, pero sin revelar qué elemento del conjunto es exactamente. Estos compromisos de conjuntos con este tipo de aperturas detalladas son la piedra angular de las criptomonedas anónimas como Zcash. En particular, proporcionamos pruebas eficientes de conocimiento cero para la apertura de acumuladores RSA, uno de los compromisos establecidos más populares. Primero, mostramos protocolos eficientes para la membresía y no membresía de un solo elemento. Luego construimos pruebas compactas de membresía de conocimiento cero para múltiples elementos, donde el tamaño de la prueba es independiente del número de elementos probados. Las dos técnicas son cualitativamente diferentes. En segundo lugar, centramos nuestra atención en los compromisos de vectores, con aperturas posicionales locales. Presentamos la noción de Agregación Incremental, en la que se pueden agregar arbitrariamente pruebas de apertura de cualquier posición en una prueba única (concisa) e inversamente desagregar una prueba de múltiples puntos en muchos. Mostramos aplicaciones de esta noción (1) para acelerar el cálculo de la prueba mediante el uso de precómputo y valores precalculados de tamaño moderado y (2) para el Almacenamiento Descentralizado Verificable. Finalmente, proporcionamos una construcción eficiente de compromisos vectoriales incrementalmente agregables a partir de grupos de orden desconocido. En tercer lugar, pasamos a los compromisos funcionales, para funciones lineales, donde uno se compromete con un vector v y luego puede abrir f(v) = y, para un f público. Construimos compromisos funcionales que admiten pruebas y parámetros públicos de tamaño constante. Con este fin, nuestra técnica principal es un protocolo novedoso y compacto de cardinalidad para un conjunto comprometido con un acumulador RSA, que a su vez se basa en una prueba de rango. Finalmente, mostramos una forma genérica de convertir cualquier compromiso de vector en un compromiso de mapa-de-valores-clave para claves arbitrarias. Un mapa-de-valores-clave se parece a un vector, pero el orden de los valores no se caracteriza por índices posteriores sino por claves arbitrarias. Los mapas-de-valores-clave son las estructuras de datos centrales en criptomonedas como Ethereum. Nuestra construcción de compromisos de mapas de valores clave es genérica y se basa en una novedosa aplicación criptográfica de Cuckoo-Hashing.
Ruben De Smet, Robrecht Blancquaert, Tom Godden, Kris Steenhaut · 5 authors
Elliptic curve cryptography is a widely deployed technology for securing digital communication. It is the basis of many cryptographic primitives such as key agreement protocols, digital signatures, and zero-knowledge proofs. Fast elliptic curve cryptography relies on heavily optimised modular arithmetic operations, which are often tailored to specific micro-architectures. In this article, we study and evaluate optimisations of the popular elliptic curve Curve25519 for ARM processors. We specifically target the ARM NEON single instruction, multiple data (SIMD) architecture, which is a popular architecture for modern smartphones. We introduce a novel representation for 128-bit NEON SIMD vectors, optimised for SIMD parallelisation, to accelerate elliptic curve operations significantly. Leveraging this representation, we implement an extended twisted Edwards curve Curve25519 back-end within the popular Rust library "curve25519-dalek". We extensively evaluate our implementation across multiple ARM devices using both cryptographic benchmarks and the benchmark suite available for the Signal protocol. Our findings demonstrate a substantial back-end speed-up of at least 20% for ARM NEON, along with a noteworthy speed improvement of at least 15% for benchmarked Signal functions.
In a world of increasing closed-source commercial machine learning models, model evaluations from developers must be taken at face value. These benchmark results-whether over task accuracy, bias evaluations, or safety checks-are traditionally impossible to verify by a model end-user without the costly or impossible process of re-performing the benchmark on black-box model outputs. This work presents a method of verifiable model evaluation using model inference through zkSNARKs. The resulting zero-knowledge computational proofs of model outputs over datasets can be packaged into verifiable evaluation attestations showing that models with fixed private weights achieve stated performance or fairness metrics over public inputs. We present a flexible proving system that enables verifiable attestations to be performed on any standard neural network model with varying compute requirements. For the first time, we demonstrate this across a sample of real-world models and highlight key challenges and design solutions. This presents a new transparency paradigm in the verifiable evaluation of private models.
To address the complexities, inflexibility, and security concerns in traditional data sharing models of the Industrial Internet of Things (IIoT), we propose a blockchain-based data sharing and privacy protection (BBDSPP) scheme for IIoT. Initially, we characterize and assign values to attributes, and employ a weighted threshold secret sharing scheme to refine the data sharing approach. This enables flexible combinations of permissions, ensuring the adaptability of data sharing. Subsequently, based on non-interactive zero-knowledge proof technology, we design a lightweight identity proof protocol using attribute values. This protocol pre-verifies the identity of data accessors, ensuring that only legitimate terminal members can access data within the system, while also protecting the privacy of the members. Finally, we utilize the InterPlanetary File System (IPFS) to store encrypted shared resources, effectively addressing the issue of low storage efficiency in traditional blockchain systems. Theoretical analysis and testing of the computational overhead of our scheme demonstrate that, while ensuring performance, our scheme has the smallest total computational load compared to the other five schemes. Experimental results indicate that our scheme effectively addresses the shortcomings of existing solutions in areas such as identity authentication, privacy protection, and flexible combination of permissions, demonstrating a good performance and strong feasibility.
Payment channels serve as an effective solution to the scalability problem of cryptocurrencies, which significantly increase transaction rates by allowing users to conduct large-scale offline transactions off-chain without posting everything to the blockchain. However, the existing payment channels lack privacy protection for the transaction amount and the linking relationship between the two parties to the transaction. Therefore, in order to address the scalability and privacy issues of cryptocurrencies such as Bitcoin, this paper proposes a zk-SNARKs-based anonymous payment channel (zk-APC), which supports an unlimited number of off-chain payments between the payer and the payee and protects the privacy of the participants. Specifically, the proposed scheme achieves relational anonymity and amount privacy for both on-chain and off-chain transactions in the payment channel through utilizing zero-knowledge proof (zk-SNARKs) and commitment schemes. This paper proves that the proposed method is more effective than similar schemes through a performance evaluation.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
A paradox of compliance and privacy exists among an increasing number of users of Decentralized Finance (DeFi). While the Financial Action Task Force (FATF) has established Travel Rules to improve transparency for financial institutions to prevent money laundering, data protection regulations like GDPR require financial institutions to maintain secrecy about customer information. The existing DeFi architecture currently solves this problem via two approaches; it either sacrifices user anonymity in order to meet the regulatory standards set forth by government entities, or creates non-transparent environments that do not hold users accountable for their actions. This paper introduces a novel DLT architecture that balances the user’s requirement for anonymity with the regulatory requirements of the financial services sector through the application of Zero-Knowledge Proofs in combination with a Permissioned DLT. By utilizing a cryptographic pipeline that allows for shielded transactions, yet provides evidence that the transaction was valid and met all relevant regulatory requirements, the architecture enables compliance with regulatory standards and maintains anonymity. Furthermore, this architecture includes protocols for selective disclosure that will enable authorized third-party auditors to audit a user’s regulatory compliance automatically without exposing PII. Experimental results demonstrate that this architecture can be deployed and tested using Hyperledger Fabric and will support both consistent performance and scalability. Specifically, experimental results demonstrate that this architecture can operate commercially at a throughput rate of 1,200 TPS, which represents less than a 35 percent increase in the consumption of computing resources compared to the corresponding rates of fully transparent architectures. Finally, the security analysis proves mathematically that this architecture fulfills the compliance requirements for preventing fraudulent activities and prevents unauthorized de-anonymization of users.
<p>To solve the problems of existing e-auction protocols such as semi-trustworthiness of outsourced third parties, collusive attacks among participants, unsatisfactory decentralized structure, and inability of public verification, we propose an efficient first-price sealed e-auction protocol under a secure multi-party computational malicious model. First, the protocol combines the additive homomorphism of the ElGamal cryptographic algorithm to achieve a decentralized structure and eliminate the problem of semi-trustworthiness of outsourced third parties; it uses (n, n) threshold encryption and decryption techniques to solve the problem of collusion attacks among participants and uses Hash-based Message Authentication Code (HMAC) technology to achieve public verifiability of auction results. Additionally, the protocol proposes a method to quickly find the maximum value of the data encoding, which can avoid multiple processing of confidential data and thus effectively reduce the number of communication rounds. The combination of zero-knowledge proof and ideal/realistic simulation paradigm proves that the protocol in this paper is resistant to up to n-1 party collusion attacks and satisfies the security of the secure multi-party computational malicious model. Finally, after theoretical analysis and simulation experiments, the protocol not only satisfies higher security performance but also has greater overall operational efficiency.</p> <p>&nbsp;</p>
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The Internet of Things (IoT) has revolutionized industries by enabling the interconnection of devices, creating opportunities for enhanced automation and real-time data analysis. However, the rapid proliferation of IoT devices has introduced significant security vulnerabilities, such as unauthorized access, data manipulation, and privacy breaches. These challenges stem from the inherent limitations of IoT devices, such as low computational power, and the reliance on centralized security models that are susceptible to single points of failure. To address these issues, this paper proposes a Blockchain-Based Secure Framework for IoT devices. Blockchain, a decentralized, immutable, and transparent distributed ledger technology, offers an effective solution for securing IoT networks. By leveraging blockchain's cryptographic features and consensus mechanisms, this framework ensures secure device authentication, data integrity, and transparent communication between IoT devices. Devices can securely authenticate themselves through blockchain-based digital identities, eliminating the need for centralized servers, thus reducing the risk of unauthorized access.Moreover, the framework guarantees data integrity by recording all IoT transactions on the blockchain, making them tamper-proof and verifiable. Blockchain's decentralized nature also mitigates the risk of Distributed Denial of Service (DDoS) attacks by removing central points of vulnerability. Privacy is enhanced through techniques such as zero-knowledge proofs, allowing users to control access to their personal data. This proposed framework not only enhances IoT security but also provides scalability, transparency, and resilience. By combining the strengths of blockchain with IoT, it offers a robust solution for secure, reliable, and privacy-preserving communication in the ever-growing IoT ecosystem. The integration of blockchain technology is poised to transform IoT security, facilitating the secure deployment and management of IoT devices across various industries.
The integration of machine learning with blockchain technology has witnessed increasing interest, driven by the vision of decentralized, secure, and transparent AI services. In this context, we introduce opML (Optimistic Machine Learning on chain), an innovative approach that empowers blockchain systems to conduct AI model inference. opML lies a interactive fraud proof protocol, reminiscent of the optimistic rollup systems. This mechanism ensures decentralized and verifiable consensus for ML services, enhancing trust and transparency. Unlike zkML (Zero-Knowledge Machine Learning), opML offers cost-efficient and highly efficient ML services, with minimal participation requirements. Remarkably, opML enables the execution of extensive language models, such as 7B-LLaMA, on standard PCs without GPUs, significantly expanding accessibility. By combining the capabilities of blockchain and AI through opML, we embark on a transformative journey toward accessible, secure, and efficient on-chain machine learning.
Bjorn Oude Roelink, Mohammed El‐Hajj, Dipti Kapoor Sarmah
Abstract This systematic literature review examines the implementation and analysis of zk‐SNARK, zk‐STARK, and bulletproof non‐interactive zero‐knowledge proof (NIZKP) protocols in privacy‐preserving applications across diverse sectors. Examining 41 research works obtained through the systematic search queries and filtering criteria published from 2015 to April 2023, we categorized findings into financial, medical, business, general, and other domains. Our analysis highlights significant variations of up to several orders of magnitude in real‐world performance across implementations utilizing NIZKP protocols. However, divergent methodologies in security analyses hindered conclusive comparisons. Addressing research gaps, our future endeavors aim to establish a real‐world benchmark for these protocols.
This paper presents an in-depth examination of privacy-enhancing methodologies in machine learning. It highlights the integration of federated learning with cutting-edge encryption techniques and explores how blockchain architectures contribute to data privacy. A major focus is on federated learning, a decentralized model training strategy, and its combination with privacy-protecting technologies like Homomorphic Encryption, Differential Privacy, and Secure Multi-Party Computation. We emphasize that federated learning naturally improves data privacy and, when paired with cryptographic methods, increases resilience against data breaches and cyber-attacks. Additionally, this study explores the potential of blockchain in enhancing data privacy. Blockchain's immutable and transparent characteristics, supplemented with shuffling technology, zero-knowledge proofs, and ring signatures, improve the confidentiality and integrity of data transactions. The paper also emphasizes the critical need for transparency and explainability in machine learning, advocating for methods that demystify the decision-making processes of ML models. This transparency is crucial for building trust and is becoming a regulatory requirement in many industries. Furthermore, the paper discusses the importance of auditing in machine learning, highlighting the need for comprehensive model validation and ethical considerations. In conclusion, the paper argues that achieving a balance 1 between functionality and privacy in ML applications is essential. It suggests that a combination of federated learning, advanced cryptographic techniques, and explainable AI principles can create effective and privacy-respecting systems.
This paper presents a cryptographic solution for establishing trust in peer-to-peer (P2P) networks, addressing issues of privacy, performance, and anonymity. Our protocol utilizes Zero-Knowledge Proofs (ZKP) for continuous trust validation during data transfers. This procedure compels each node to continually demonstrate its integrity, significantly decreasing the potential for network at- tacks. Upon evaluation, the protocol proved to be highly scalable and efficient, expanding network reach without requiring additional control messages. This result validates the protocol’s robustness, suggesting its potential use in larger and more intricate P2P network architectures.
Foteini Baldimtsi, Konstantinos Kryptos Chalkias, Yan Ji, Jonas Lindstrøm · 9 authors
For many users, a private key based wallet serves as the primary entry point to blockchains. Commonly recommended wallet authentication methods, such as mnemonics or hardware wallets, can be cumbersome. This difficulty in user onboarding has significantly hindered the adoption of blockchain-based applications. We develop zkLogin, a novel technique that leverages identity tokens issued by popular platforms (any OpenID Connect enabled platform e.g., Google, Facebook, etc.) to authenticate transactions. At the heart of zkLogin lies a signature scheme allowing the signer to sign using their existing OpenID accounts and nothing else. This improves the user experience significantly as users do not need to remember a new secret and can reuse their existing accounts. zkLogin provides strong security and privacy guarantees. Unlike prior works, zkLogin's security relies solely on the underlying platform's authentication mechanism without the need for any additional trusted parties (e.g., trusted hardware or oracles). As the name suggests, zkLogin leverages zero-knowledge proofs (ZKP) to ensure that the sensitive link between a user's off-chain and on-chain identities is hidden, even from the platform itself. zkLogin enables a number of important applications outside blockchains. It allows billions of users to produce \textit{verifiable digital content leveraging their existing digital identities}, e.g., email address. For example, a journalist can use zkLogin to sign a news article with their email address, allowing verification of the article's authorship by any party. We have implemented and deployed zkLogin on the Sui blockchain as an additional alternative to traditional digital signature-based addresses.
The increasing complexity of identity verification in U.S. banking and fintech ecosystems has highlighted thelimitations of traditional centralized Know Your Customer (KYC) processes, which often involve redundantdata collection, slow onboarding, and increased risk of data breaches. This study explores the design andimplementation of a Decentralized Identity (DID) architecture to enable secure, privacy-preserving, and usercentric KYC. By leveraging self-sovereign identity (SSI) principles, verifiable credentials (VCs), andcryptographic proofs, the proposed framework allows individuals to control their identity data while banks,fintechs, and regulatory authorities can authenticate users efficiently and compliantly. The architectureintegrates permissioned networks, identity wallets, credential issuers, and verifier nodes, supportinginteroperability with existing financial systems. Security, privacy, and regulatory compliance—including AML,FinCEN, and OFAC requirements—are embedded through robust cryptography, zero-knowledge proofs, andselective disclosure mechanisms. The study concludes that DID-enabled KYC can streamline onboarding,reduce operational costs, enhance user privacy, and strengthen overall financial ecosystem trust, providing aviable path for next-generation identity verification in U.S. banking and fintech.
With the widespread application of blockchain technology, various range proof protocols based on zero-knowledge proofs have been proposed. However, existing range proof protocols suffer from issues such as high communication overhead and computational complexity. Therefore, this paper introduces an efficient and secure Zero-Knowledge Set Membership Proof Protocol (ZSMPP) to address these challenges. Building upon improvements to the proof structure of range proof protocols, the paper integrates the SM2 identity-based digital signature algorithm, effectively avoiding the time-consuming bilinear pairing operations and reducing computational costs. The proposed protocol offers an efficient and secure solution for the given problem. Experimental results demonstrate that, compared to protocols proposed by Bootle, Deng, Mao, and others, the protocol presented in this paper exhibits superior computational efficiency, providing an efficient and secure solution for data security and individual privacy protection in the digital age.
Marta Irene García Cid, Dileepsai Bodanapu, Alberto Gatto, Paolo Martelli · 6 authors
A new interactive quantum zero-knowledge protocol for identity authentication implementable in currently available quantum cryptographic devices is proposed and demonstrated. The protocol design involves a verifier and a prover knowing a pre-shared secret, and the acceptance or rejection of the proof is determined by the quantum bit error rate. It has been implemented in modified Quantum Key Distribution devices executing two fundamental cases. In the first case, all players are honest, while in the second case, one of the users is a malicious player. We demonstrate an increase of the quantum bit error rate around 25% in the latter case compared to the case of honesty. The protocol has also been validated for distances from a back-to-back setup to more than 60 km between verifier and prover. The security and robustness of the protocol has been analysed, demonstrating its completeness, soundness and zero-knowledge properties.
Andrea Flamini, Giada Sciarretta, Mario Scuro, Amir Sharif · 6 authors
Verifiable credentials are a digital analogue of physical credentials. Their authenticity and integrity are protected by means of cryptographic techniques, and they can be presented to verifiers to reveal attributes or even predicates about the attributes included in the credential. One way to preserve privacy during presentation consists in selectively disclosing the attributes in a credential. In this paper we present the most widespread cryptographic mechanisms used to enable selective disclosure of attributes identifying two categories: the ones based on hiding commitments - e.g., mdl ISO/IEC 18013-5 - and the ones based on non-interactive zero-knowledge proofs - e.g., BBS signatures. We also include a description of the cryptographic primitives used to design such cryptographic mechanisms. We describe the design of the cryptographic mechanisms and compare them by performing an analysis on their standard maturity in terms of standardization, cryptographic agility and quantum safety, then we compare the features that they support with main focus on the unlinkability of presentations, the ability to create predicate proofs and support for threshold credential issuance. Finally we perform an experimental evaluation based on the Rust open source implementations that we have considered most relevant. In particular we evaluate the size of credentials and presentations built using different cryptographic mechanisms and the time needed to generate and verify them. We also highlight some trade-offs that must be considered in the instantiation of the cryptographic mechanisms.
Electronic tickets (e-tickets) are gradually being adopted as a substitute for paper-based tickets to bring convenience to customers, corporations, and governments. However, their adoption faces a number of practical challenges, such as flexibility, privacy, secure storage, and inability to deploy on IoT devices such as smartphones. These concerns motivate the current research on e-ticket systems, which seeks to ensure the unforgeability and authenticity of e-tickets while simultaneously protecting user privacy. Many existing schemes cannot fully satisfy all these requirements. To improve on the current state-of-the-art solutions, this paper constructs a blockchain-enhanced privacy-preserving e-ticket system for IoT devices, dubbed PriTKT, which is based on blockchain, structure-preserving signatures (SPS), unlinkable redactable signatures (URS), and zero-knowledge proofs (ZKP). It supports flexible policy-based ticket purchasing and ensures user unlinkability. According to the data minimization and revealing principle of GDPR, PriTKT empowers users to selectively disclose subsets of (necessary) attributes to sellers as long as the disclosed attributes satisfy ticket purchasing policies. In addition, benefiting from the decentralization and immutability of blockchain, effective detection and efficient tracing of double spending of e-tickets are supported in PriTKT. Considering the impracticality of existing e-tickets schemes with burdensome ZKPs, we replace them with URS/SPS or efficient ZKP to significantly improve the efficiency of ticket issuing and make it suitable for use on smartphones.
Blockchain technology offers a promising way to improve business processes by providing a secure and transparent transaction platform. However, using this technology brings its own set of challenges, especially when trying to balance user privacy with legal and regulatory needs. This article explores the challenges of keeping user information private, adhering to regulatory frameworks, and fulfilling legal requirements on the blockchain. A key point in this research is the challenge of keeping or maintaining confidentiality while being transparent. The article also discusses the issues of applying legal rules to a system not controlled by one central authority, the risks of privacy and security breaches, and the need to follow data protection laws. The article highlights how some blockchain-based companies have tackled these challenges, mainly through smart blockchain management and innovative technology, by looking at real-world examples from major companies like IBM, Bitpay, Ripple, and Coinbase. The systematic literature review (SLR) methodology involved reviewing literature from the past 15 years (2008-2023) from trusted sources like Google Scholar, ACM Digital Library, IEEE, Springer, and Science Direct. The findings indicate that cutting-edge technologies prioritizing privacy, such as zero-knowledge proofs, ring signatures, and encryption methods, would enable Bitcoin (BTC) platform operations to maintain or balance privacy and transparency. Furthermore, the study indicates the importance of clear privacy guidelines, adhering to relevant regulations, working closely with regulators and law enforcement, and educating users. In summary, it is crucial to approach blockchain carefully, prioritizing user privacy while meeting all legal and regulatory requirements.
Wooyoung Son, Soonhong Kwon, Sung-Heun Oh, Jong‐Hyouk Lee
As the demand and diversity of digital content increase, consumers now have simple and easy access to digital content through Over-the-Top (OTT) services. However, the rights of copyright holders remain unsecured due to issues with illegal copying and distribution of digital content, along with unclear practices in copyright royalty settlements and distributions. In response, this paper proposes an automated OTT service copyright distribution management system using the Open Digital Rights Language (ODRL) to safeguard the rights of copyright holders in the OTT service field. The proposed system ensures that the rights to exercise copyright transactions and agreements, such as trading of copyright, can only be carried out when all copyright holders of a single digital content agree based on the Threshold Schnorr Digital Signature. This approach takes into account multiple joint copyright holders, thereby safeguarding their rights. Furthermore, it ensures fair and transparent distribution of copyright royalties based on the ratio information outlined in ODRL. From the user’s perspective, the system not only provides services proactively based on the rights information specified in ODRL, but also employs zero-knowledge proof technology to handle sensitive information in OTT service copyright distribution, thereby addressing existing privacy concerns. This approach not only considers joint copyright holders, but also demonstrates its effectiveness in resolving prevalent issues in current OTT services, such as illegal digital content replication and distribution, and the unfair settlement and distribution of copyright royalties. Applying this proposed system to the existing OTT services and digital content market is expected to lead to the revitalization of the digital content trading market and the establishment of an OTT service environment that guarantees both vitality and reliability.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Due to complex network threats, network security faces unprecedented challenges in a rapidly changing environment. These details highlight the importance of cryptography in protecting networks from today's threats. The development of technology has led to the increase in connected devices, the expansion of parking areas and the need for security measures. Honest and confidential information is protected by encryption technology using complex methods and algorithms. The brief reviews state-of-the-art cryptographic techniques and highlights the importance of quantum-resistant mechanisms against the threat of quantum computing. It explores how cryptography can be used together with technologies such as blockchain, artificial intelligence and the Internet of Things, and emphasizes its importance in ensuring the security of these areas. It envisions the development and implementation of post-quantum cryptography, covers concepts such as homomorphic encryption and zero-knowledge proofs, and addresses issues of cryptographic efficiency and creative control. It aims to protect networks from new threats and ensure secure data exchange by meeting the need for strong cryptographic protection in the evolving business environment.