Blockchain technology is a Distributed Ledger Technology (DLT) where the digital information is stored across multiple computers and not centralized.Each system stores a copy of DLT to avoid single point of failure.Blockchain stores the information in blocks.All copies are validated and updated simultaneously.There are four main types of blockchain, they are Private / Permissioned, Public / Permissionless, Hybrid and Consortium.Corda is a distributed ledger open-source platform, it was introduced by R3 consortium (R3CEV LLC).It is not a public blockchain, based on agreement network and Peer to Peer (P2P) connections.No native cryptocurrency.Tech stack platform based out of JVM written in Koltin.
Minghui Zheng, Shicheng Huang, Deju Kong, Xing Fu · 6 authors
Linkable ring signatures are a type of ring signature scheme that can protect the anonymity of signers while allowing the public to verify whether the same signer has signed the same message multiple times. This functionality makes linkable ring signatures suitable for applications such as cryptocurrencies and anonymous voting systems, achieving the dual goals of identity privacy protection and misuse prevention. However, existing post-quantum linkable ring signature schemes often suffer from issues such as excessive linear data growth the adoption of post-quantum signature algorithms, and high circuit complexity resulting from the use of post-quantum zero-knowledge proof protocols. To address these issues, a logarithmic-size post-quantum linkable ring signature scheme based on aggregation operations is proposed. The scheme constructs a Merkle tree from ring members' public keys via a hash algorithm to achieve logarithmic-scale signing and verification operations. Moreover, it introduces, for the first time, a post-quantum aggregate signature scheme to replace post-quantum zero-knowledge proof protocols, thereby effectively avoiding the construction of complex circuits. Scheme analysis confirms that the proposed scheme meets the correctness requirements of linkable ring signatures. In terms of security, the scheme satisfies the anonymity, unforgeability, and linkability requirements of linkable ring signatures. Moreover, the aggregation process does not leak information about the signing members, ensuring strong privacy protection. Experimental results demonstrate that, when the ring size scales to 1024 members, our scheme outperforms the existing Dilithium-based logarithmic post-quantum ring signature scheme, with nearly 98.25% lower signing time, 98.90% lower verification time, and 99.81% smaller signature size.
Shaoyu Li, Hexuan Yu, Md Mohaimin Al Barat, Yang Xiao · 6 authors
With the rise of decentralized finance, fiat-to-cryptocurrency exchange platforms have become popular entry points into the cryptocurrency ecosystem. However, these platforms frequently fail to ensure adequate privacy protection, as evidenced by real-world breaches that exposed personally identifiable information (PII) and crypto addresses. Such leaks enable adversaries to link real-world identities to cryptocurrency transactions, undermining the presumed anonymity of cryptocurrency use. We propose FC-GUARD, a privacy-preserving exchange system designed to preserve user anonymity without compromising regulatory compliance in the exchange of fiat currency for cryptocurrencies. Leveraging verifiable credentials and zero-knowledge proof techniques, FC-GUARD enables fiat-to-cryptocurrency exchanges without revealing users' PII or fiat account details. This breaks the linkage between users' real-world identities and their cryptocurrency addresses, thereby upholding anonymity, a fundamental expectation in the cryptocurrency ecosystem. In addition, FC-GUARD complies with key regulations over cryptocurrency usage, such as know-your-customer requirements and auditability for tax reporting obligations by integrating a lawful de-anonymization mechanism that allows the auditing authority to identify misbehaving users. This ensures regulatory compliance while defaulting to privacy protection. We implement our system on both desktop and mobile platforms, and our evaluation shows its feasibility for practical deployment.
Zhichao Wang, Xudong Zhu, Xinxuan Zhang, Yi Deng · 5 authors
Abstract Time-release cryptography is a flourishing research area with a long history and has been extensively studied. In this work, we enrich it by introducing a novel concept: a time-release zero-knowledge proof (TRZKP). A TRZKP is a non-interactive zero-knowledge proof that allows one to publish a proof for a given relation $$R_\mathcal {L}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>R</mml:mi> <mml:mi>L</mml:mi> </mml:msub> </mml:math> , such that anyone can only finish the verification after time $$\textbf{T}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> by performing a sequential computation. This work formalizes the concept of TRZKP and presents light constructions for the time-release version of any NIZK obtained from a public-coin protocol via Fiat-Shamir transformation. TRZKPs can be applied to provide time-release authentication, for example, they can be employed to construct verifiable timed signatures (VTS), introduced by Thyagarajan et al. (CCS’20). Through both theoretical and practical analysis, our construction has advantages over existing VTS for Fiat-Shamir signatures. Specifically, when instantiated with Shnorr signature, our VTS signing time remains basically unchanged as the delay time grows, and is preferable for longer delay times; our VTS verification time is significantly small (on the level of milliseconds, while existing works on the level of seconds), and our VTS size is 67 times smaller than the state-of-the-art. It also has the time-verifiability property, which ensures the signature is recoverable after the specified time.
With the rapid development of online aquatic product trading, traditional centralized platforms are facing increasing pressure in terms of data security, privacy protection, and trust. Problems such as tampering with transaction records, weak identity authentication, privacy leakage, and the difficulty of balancing matching efficiency with security limit the further development of these platforms. To address these issues, this paper proposes a blockchain-based identity authentication and access control scheme for online aquatic product trading. The scheme first introduces a dual authentication mechanism that combines a verifiable random function with a Schnorr-based zero-knowledge proof, providing strong decentralized identity verification and resistance to replay attacks. It then designs a dynamic access control strategy based on a multi-dimensional reputation model, which converts user behavior, attributes, and historical transaction performance into a comprehensive trust score used to determine fine-grained access rights. In addition, an AES-PEKS hybrid encryption method is employed to support encrypted keyword search and order matching while protecting the confidentiality of order data. This paper implements a multi-channel architecture for aquatic product trading prototype system on Hyperledger Fabric. This system separates registration, order processing, and reputation management into different channels to improve concurrency and enhance privacy protection. Security analysis shows that the proposed solution effectively defends against replay attacks, key leaks, data tampering, and privacy theft. Performance evaluation further demonstrates that, compared to a single-chain architecture, the multi-channel design, while increasing security mechanisms, maintains a stable throughput of approximately 223 tx/s even when concurrency reaches 600–800 tx/s, ensuring normal operation of the trading system. These results indicate that this solution provides a practical technical approach and system-level reference for building secure, reliable, and efficient online aquatic product trading platforms.
Abstract The emerging growth of Quantum computing has significant challenges to change the classical cryptographic protocols, the security of AI–Blockchain systems to provide long-term security and provide federated learning (FL) for current cryptographic systems. This paper introduces a new framework as Quantum-Resistant Federated AI on Blockchain (QFAIB) that integrates Post-Quantum Cryptography (PQC) algorithms with real-time Federated AI Learning (FAIL) on distributed ledgers creation. The proposed QFAIB ensures end-to-end data security and confidentiality, decentralized trust, and adaptive intelligence, resistant to quantum decryption attacks. Through the integration of hybridization of CRYSTALS-Kyber encryption to create challenging task, that makes the Dilithium digital signatures, and Zero-Knowledge Proofs (ZKP) for privacy-preserving model validation and decentralized federated AI models, the proposed QFAIB compared with baseline and evaluated as the performance metrics as data integrity verification accuracy (DIVA), auditing efficiency (AE), quantum resistance efficiency (QRE), privacy leakage reduction (PLR) and throughput (TT) in multi-cloud and IoT environments and this work proved that real time distributed ledger creations.
The increasing importance of privacy and secure communication in distributed environments has fueled research into innovative solutions that combine data concealment and tamper-resistant recordkeeping. This article presents a logically structured architectural framework for covert steganographic communication, utilizing the Microsoft Azure web3 ecosystem as its foundation. The motivation behind this research stems from the limitations of traditional steganography and blockchain technologies when used independently, particularly in addressing the challenges of operational transparency, scalability, and robust data protection. To bridge these gaps, the proposed system integrates Azure Blockchain Development Kit with other Azure native services to provide a unified architecture. This research article introduces a pioneering architectural framework designed to facilitate covert steganographic communication through blockchain technologies, with a focus on leveraging the Microsoft Azure web3 ecosystem. By integrating Azure Blockchain Development Kit (BDK), Azure Confidential Ledger, Azure Blockchain Services, and Azure Blockchain Workbench with Open Steganography solutions deployed on Azure Virtual Machines (VM), the proposed system aims to achieve secure, confidential, and unobtrusive data exchange. The research methodology encompasses a comprehensive literature review, system design, implementation, and rigorous security analysis, followed by experimental evaluation on cloud infrastructure. By leveraging the strengths of Azure’s blockchain and confidential ledger capabilities alongside advanced steganographic techniques, this study demonstrates a practical approach to achieving secure, confidential, and unobtrusive data exchange. The findings confirm the feasibility and effectiveness of the proposed solution, highlighting its potential to facilitate adaptive, scalable, and privacy-preserving covert communication networks. In conclusion, this work charts new directions for integrating blockchain and steganography within cloud-native platforms, offering enhanced privacy and security for sensitive communications in distributed settings.
Current research on cryptocurrency dual-offline payment systems has garnered significant attention from both academia and industry, owing to its potential payment feasibility and application scalability in extreme environments and network-constrained scenarios. However, existing dual-offline payment schemes exhibit technical limitations in privacy preservation, failing to adequately safeguard sensitive data such as payment amounts and participant identities. To address this, this paper proposes a privacy-preserving dual-offline payment method utilizing a cryptographic challenge-response mechanism. The method employs zero-knowledge proof technology to cryptographically protect sensitive information, such as the payer’s wallet balance, during identity verification and payment authorization. This provides a technical solution that balances verification reliability with privacy protection in dual-offline transactions. The method adopts the payment credential generation and credential verification mechanism, combined with elliptic curve cryptography (ECC), to construct the verification protocol. These components enable dual-offline functionality while concealing sensitive information, including counterparty identities and wallet balances. Theoretical analysis and experimental verification on 100 simulated transactions show that this method achieves an average payment generation latency of 29.13 ms and verification latency of 25.09 ms, significantly outperforming existing technology in privacy protection, computational efficiency, and security robustness. The research provides an innovative technical solution for cryptocurrency dual-offline payment, advancing both theoretical foundations and practical applications in the field.
The digitization of medical records in the healthcare sector demands robust mechanisms to ensure data confidentiality, integrity, and privacy. This paper proposes an innovative multi-factor authentication (MFA) mechanism that leverages smart contracts and blockchain technology to secure the tracking of medical records. The proposed system, named Blockchain Authentication with Zero-Knowledge Proof (BAZKP), provides a tamper-proof environment for storing and accessing records while preserving users’ personally identifiable information (PII). A key novelty of BAZKP lies in storing only the character count structure of passwords rather than the actual credentials, combined with zero-knowledge proofs (ZKP) to verify identity without exposing sensitive data. This hybrid blockchain/ZKP approach addresses limitations of centralized and hardware-based solutions, reducing vulnerabilities while avoiding the cost and usability constraints of dedicated hardware systems. The system was implemented and tested on a private Ethereum testnet, with a proof-of-concept application developed using Solidity, Web3.js, and MetaMask. Performance evaluation over 100 transactions for core operations (registration, login, and password reset) demonstrated practical viability: registration incurred the highest latency (≈4500 ms) and gas consumption (≈120,000 gas), while login and reset operations were more efficient (≈4000 ms/80,000 gas and ≈3500 ms/60,000 gas, respectively). Comparative security analysis against existing MFA methods—including 2FA, hardware tokens, and biometrics—confirms that BAZKP provides superior privacy protection through decentralization and ZKP, without the cost and usability drawbacks of hardware-based solutions. Overall, this approach enhances trust in digital health systems by offering a secure, transparent, and privacy-preserving authentication framework for medical data, representing a significant advancement in digital healthcare security. Keywords: Blockchain; Multi-Factor Authentication; Smart Contracts; Zero-Knowledge Proof; Medical Record Security.
Introduction Digital identity infrastructures used in electronic passports, national eID schemes, and federated authentication systems rely predominantly on centralised registries and classical public key cryptography. These architectures enable large-scale identity correlation, mass data aggregation, and single points of compromise, while remaining vulnerable to quantum attacks against RSA and elliptic-curve cryptography. There is no deployed identity framework that simultaneously provides post-quantum security, cryptographic privacy guarantees, and decentralised trust. Methods This study proposes a quantum-proof digital passport architecture combining lattice-based post-quantum cryptography, decentralised blockchain identifiers, and transformer-based decentralised artificial intelligence. The framework employs NIST-aligned post-quantum key encapsulation and digital signatures, zero-knowledge proofs for selective disclosure of identity attributes, and homomorphic encryption for encrypted identity verification. Blockchain oracles and decentralised identifiers enforce credential integrity and auditability without reliance on central identity providers. Transformer attention mechanisms support adaptive identity validation while preventing persistent identity profiling. Results Architectural analysis shows that the proposed system prevents quantum-enabled credential forgery, retrospective decryption, and cross-service identity linkability. Zero-knowledge verification removes plaintext exposure of personal data, and decentralised credential control eliminates central compromise vectors. The design remains interoperable with existing passport and eID infrastructures. Discussion The results demonstrate that secure post-quantum digital identity requires the combined application of quantum-resistant cryptography, decentralised governance, and cryptographic privacy enforcement.
Open access
Cryptography and Data Security
Quantum Computing Algorithms and Architecture
Physical Unclonable Functions (PUFs) and Hardware Security
Journal of Theoretical and Applied Information Technology
With the growing volume of health information it has become common practice to protect the patient identity while maintaining convenient access to the data. Due to varying flow of cyber security threats, traditional solutions never manage to get flexible access to data without compromising with overflow of data. To overcome these challenges focusing on patient data protection, in this paper, we propose a new Hybrid Integrated Hashing approach entitled "Dynamic Adaptive Hash-Block Access Control (DAHBAC) framework" using blockchain based advanced data access control mechanism. The dynamic multi factor hashing scheme can change in response to the current Vulnerability of data and access patterns, whereas data access control refers to leverage blockchain's immutability and decentralized structure that helps protecting patient privacy while allowing authorized persons to read. The dynamic hashing method prevents intruder attempts by making hash and easy to calculate but requiring real-time modification of the hash for access protection. This is made possible by harnessing the application of zero-knowledge proofs (ZKP) within the frame of blockchain to enable verification of information when there is no disclosure of the data. Compared with the conventional methods, testing of prototype in a health care organization resulted in 92% on attempts by unauthorized workers to enter the system and 7% increasing data retrieval rate. These findings shows that the proposed model is a perfect patient data protection pattern in ehealth systems, because it is not only secures patients data but also enhances the accessibility and scalability to handle more clients. It is enabled by the use of zero-knowledge proofs (ZKP) in combination with blockchain technology to verify information, while keeping the information secret.
Hasina Andriambelo, Hery Zo Andriamanohisoa, Naghmeh Moradpoor
Federated learning enables collaborative model training without sharing raw data, but practical deployments increasingly require verifiable guarantees that clients compute updates correctly. Zero-knowledge proofs can provide such guarantees, yet existing approaches face scalability limits due to the combined cost of polynomial commitments and fast Fourier transform (FFT) intensive verification. Pairing-based schemes offer compact proofs but incur high prover and verifier overhead, while hash-based constructions reduce algebraic cost at the expense of rapidly growing proof sizes. This paper proposes Hybrid-Commit, a polynomial commitment architecture for Binius zero-knowledge proofs that aligns cryptographic primitives with the algebraic structure of federated learning workloads. The scheme separates verification into additive and multiplicative phases: linear aggregation is handled using batched additive commitments optimized for binary fields, while non-linear constraints are verified via hash-based commitments over sparsely selected FFT domains. Proofs from multiple clients are combined through recursive aggregation while preserving non-interactivity. Experiments demonstrate scalability in prover time and proof size (near-constant prover time across 4–11 clients; 160 bytes per client representing 341× and 813× reductions vs. FRI-PCS and Orion), although verification time (762 ms per client) does not scale favorably, making the scheme suitable for bandwidth-constrained scenarios. The scheme achieves under 2% end-to-end training overhead with no impact on model accuracy, indicating that workload-aware commitment design can improve specific scalability dimensions of zero-knowledge verification in federated learning systems.
Defensive publication establishing prior art for proof-first digital identity systems using prime-indexed state evolution, zero-knowledge proofs, and silence-by-default semantics. This specification defines the Meta-Theorem of Prime Identity (MTPI), an architectural framework requiring cryptographic proof for every state transition. Core components include: Prime-Indexed Recursive Tensor Mathematics (PIRTM) with contractive dynamics guarantee; prime-gated activation with drift bounds δ(t) ≤ 0.3; Conscious Sovereignty Layer (CSL) with ethical tensor field commutation relations; Archivum append-only audit schema; and conformance requirements including Surveillance Fork detection. Reference implementations provided in Solidity and Circom 2.1. Mathematical foundations, alternative embodiments, and public domain designations included for maximum prior art scope. Keywords: zero-knowledge proofs, prime-indexed identity, verifiable computation, AI safety, defensive publication, proof-first computing, MTPI, PIRTM, CSL
Open access
2 source records
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Zero-Knowledge (ZK) proof systems are cryptographic protocols that can (with overwhelming probability) demonstrate that the pair $(X, W)$ is in a relation $R$ without revealing information about the private input $W$. This membership checking is captured by a complex arithmetic circuit: a set of polynomial equations over a finite field. ZK programming languages, like Noir, have been proposed to simplify the description of these circuits. A developer can write a Noir program using traditional high-level constructs that can be compiled into a lower-level ACIR (Abstract Circuit Intermediate Representation), which is essentially a high-level description of an arithmetic circuit. In this paper, we formalise some of the ACIR language using SMT-LIB and its extended theory of finite fields. We use this formalisation to create an open-source formal verifier for the Noir language using the SMT solver cvc5. Our verifier can be used to check whether Noir programs behave appropriately. For instance, it can be used to check whether a Noir program has been properly constrained, that is, the finite-field polynomial equations generated truly capture the intended relation. We evaluate our verifier over 4 distinct sets of Noir programs, demonstrating its practical applicability and identifying a hard-to-check constraint type that charts an improvement path for our verification framework.
The Internet of Medical Things (IoMT) enables real-time health monitoring and intelligent clinical decision-making by continuously collecting and processing sensitive physiological data from wearable, implantable, and edge-connected devices. However, this data aggregation paradigm introduces critical privacy and security challenges, including data leakage, aggregator misbehavior, and adversarial attacks, while existing frameworks often fail to simultaneously ensure confidentiality, verifiability, and efficiency. To address these limitations, we propose MedGuard, a novel end-to-end secure data aggregation framework for IoMT that synergistically integrates Fully Homomorphic Encryption (FHE) based on the CKKS scheme and Groth16 zero-knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs). MedGuard enables healthcare providers to perform complex analytical queries, such as statistical analysis, anomaly detection, and trend forecasting, directly on encrypted data without decryption, ensuring compliance with privacy regulations. By allowing edge nodes to generate cryptographic proofs of correct computation and enabling cloud-based verification, MedGuard eliminates reliance on trusted intermediaries and mitigates insider threats. Our comprehensive evaluation, conducted in a high-fidelity OMNeT++ 6.0.1 simulation environment with 1,000 IoMT devices, 100 edge nodes, and an Amazon EC2 c5.4xlarge cloud server, uses a hybrid dataset combining real-world and GMM-augmented synthetic data. Results show that MedGuard achieves an end-to-end latency of 64.8 ms, a 13.3% improvement over state-of-the-art baselines, communication efficiency of 1.465 GB/s, per-query energy consumption of 1.489 mJ, and sustained throughputs of 1,200 packets/s, 120 aggregates/s, and 1,200 queries/s. These performance gains, combined with a robust [Formula: see text] security level, demonstrate that MedGuard delivers scalable, verifiable, and privacy-preserving analytics for next-generation smart healthcare systems.
A sharing framework based on Zero-Knowledge Proof (ZKP) and Proxy Re-encryption (PRE) technologies offers a promising solution for sharing Student Electronic Academic Records (SEARs). As core credentials in the education sector, student records are characterized by strong identity binding, the need for long-term retention, frequent cross-institutional verification, and sensitive information. Compared with electronic health records and government archives, they face more complex security, privacy protection, and storage scalability challenges during sharing. These records not only contain sensitive data such as personal identity and academic performance but also serve as crucial evidence in key scenarios such as further education, employment, and professional title evaluation. Leakage or tampering could have irreversible impacts on a student’s career development. Furthermore, traditional blockchain technology faces storage capacity limitations when storing massive academic records, and existing general electronic record sharing solutions struggle to meet the high-frequency verification demands of educational authorities, universities, and employers for academic data. This study proposes a dedicated sharing framework for students’ electronic academic records, leveraging PRE technology and the distributed ledger characteristics of blockchain to ensure transparency and immutability during sharing. By integrating the InterPlanetary File System (IPFS) with Ethereum Smart Contract (SC), it addresses blockchain storage bottlenecks, enabling secure storage and efficient sharing of academic records. Relying on optimized ZKP technology, it supports verifying the authenticity and integrity of records without revealing sensitive content. Furthermore, the introduction of gate circuit merging, constant folding techniques, Field-Programmable Gate Array (FPGA) hardware acceleration, and the efficient Bulletproofs algorithm alleviates the high computational complexity of ZKP, significantly reducing proof generation time. The experimental results demonstrate that the framework, while ensuring strong privacy protection, can meet the cross-scenario sharing needs of student records and significantly improve sharing efficiency and security. Therefore, this method exhibits superior security and performance in privacy-preserving scenarios. This framework can be applied to scenarios such as cross-institutional academic certification, employer background checks, and long-term management of academic records by educational authorities, providing secure and efficient technical support for the sharing of electronic academic credentials in the digital education ecosystem.
We propose a novel digital signature cryptosystem that exploits the concept of the brute-force problem. To ensure the security of the cryptosystem, we employed several mechanisms: sharing a common secret for factorable permutations, associating permutations with the message being signed, and confirming knowledge of the shared secret using a zero-knowledge proof. We developed a secret-sharing theory based on homomorphic matrix transformations for factorized permutations. The inverse matrix transformation for computing the shared secret is determined by secret parameters, which results in incompletely defined functionality and gives rise to a brute-force cryptanalysis problem. Randomization of session keys using a message hash and random parameters guarantees the uniqueness of each signature, even for identical messages. We employed a zero-knowledge authentication protocol to confirm knowledge of the shared secret, thereby protecting the verifier against unauthorized signature imposition. The LINEture cryptosystem is built on linear matrix algebra and does not rely on a computationally hard problem. High security is achieved through the appropriate selection of matrix transformation dimensions. Matrix computations potentially offer low operational costs for signature generation and verification.
Chimeremma Sandra Amadi, Simeon Okechukwu Ajakwe, Taesoo Jun
Secure and auditable data sharing in large-scale Internet of Things (IoT) environments remains a significant challenge due to weak trust coordination, limited scalability, and susceptibility to emerging quantum attacks. This study introduces a hybrid blockchain-based framework that integrates post-quantum cryptography with intelligent anomaly detection to ensure end-to-end data integrity and resilience. The proposed system utilizes Hyperledger Fabric for permissioned device lifecycle management and Ethereum for public auditability of encrypted telemetry, thereby providing both private control and transparent verification. Device identities are established using quantum-entropy-seeded credentials and safeguarded with lattice-based encryption to withstand quantum adversaries. A convolutional long short-term memory (CNN–LSTM) model continuously monitors device behavior, facilitating real-time trust scoring and autonomous revocation via smart contract triggers. Experimental results demonstrate 97.4% anomaly detection accuracy and a 0.968 F1-score, supporting up to 1000 transactions per second with cross-chain latency below 6 s. These findings indicate that the proposed architecture delivers scalable, quantum-resilient, and computationally efficient data sharing suitable for mission-critical IoT deployments.
We present Y.I.N.-LLM, a privacy-preserving training architecture for Large Language Models that mathematically guarantees non-memorization of training data. The core innovation is the mandatory DP→ZK→HE ordering (Differential Privacy → Zero-Knowledge Proof → Homomorphic Encryption) applied to transformer gradients during training. Key results: (1) 2.3% accuracy loss at ε=1.0 privacy versus 15-40% with standard DP-SGD; (2) zero extractable training data across all tested attack vectors; (3) native GDPR Article 17 "right to be forgotten" compliance via cryptographic gradient subtraction; (4) EU AI Act Article 50 transparency compliance through verifiable privacy proofs. The Non-Memorization Theorem establishes that for any model M trained with Y.I.N.-LLM parameters (ε, δ), the probability of verbatim reproduction is bounded: P[M outputs y | x ∈ training] ≤ e^ε · P[M outputs y | x ∉ training]. This transforms copyright defense from argument to mathematics. Y.I.N.-LLM addresses the $10B+ memorization litigation crisis (NYT v. OpenAI, Getty v. Stability AI, Authors Guild v. OpenAI) by providing the first mathematically verifiable non-memorization guarantee with practical accuracy preservation. Patent Protected: U.S. Provisional Application 63/946,118 (filed December 21, 2025).
Yuxin Xia, Ziyang Ji, Jie Zhang, Wanxin Li · 7 authors
Abstract Non-Fungible Token (NFT) creators use digital signatures to ensure the ownership, authenticity, integrity, and nonrepudiation of their digital works. However, if the private key is compromised, an attacker can generate unauthorized NFTs by using the creator’s private key to issue valid signatures. These valid but unauthorized signatures will be accepted in the NFT market and cannot be revoked. Even if the NFT creators update their private-public key pairs, they cannot deny the NFTs generated by the attacker. To mitigate these risks, we propose revocable signature by introducing commitment mechanism and an Auxiliary Embedded Key ( AEK ) into the signature, while the regular verification process does not involve this AEK . If a valid but unauthorized signature is detected and needs to be revoked, AEK will be disclosed to perform the revocation operation. To illustrate the application of revocable signatures in NFT, we design and implement a revocable Elliptic Curve Digital Signature Algorithm (ECDSA) scheme with provable security. Experimental evaluations on the FIPS-recommended elliptic curves show that the performance of revocable ECDSA is comparable to the basic ECDSA, with additional 0.0303 s (P-256 curve) and 0.15 USD gas fee in Remix VM for revoking a signature.
Open access
Cryptography and Data Security
Cryptography and Residue Arithmetic
Physical Unclonable Functions (PUFs) and Hardware Security
SNARKs enable compact proofs that an NP statement is true and that the prover knows a valid witness. They have become a key building block in modern smart contract applications, including rollups and privacy-focused cryptocurrencies. In the widely used Groth16 framework, however, long statements incur high costs. A common workaround is to pass the statement’s hash to the SNARK and move the statement into the witness. The smart contract then hashes the statement first, and the circuit that is proven additionally checks consistency of the hash and the statement. Unfortunately, virtually any hash function is expensive to call either in a smart contract (in terms of gas) or in the proven circuit (in terms of prover time). We demonstrate a novel solution to this dilemma, which we call hybrid compression. Our method allows us to use two different hash functions—one optimized for the proof circuit, and another optimized for on-chain verification—thereby combining the efficiency advantages of both. We define a clean and simple security property of the two hash functions to which our security reduces in the standard model, namely, joint UHF hardness. We then show the plausibility of this assumption in the random oracle model. Our benchmarks show that it achieves near-optimal performance in both gas usage and prover time. As an example, compressing an 8 KB statement with our approach results in a 10-second prover time and a smart contract spending 270K gas, whereas the existing approaches either need a much longer proof generation (290 seconds for SHA-256 hashing) or a much more expensive contract (5M gas for Poseidon hashing). Along the way, we develop a two-party protocol of independent interest in communication complexity: an efficient deterministic method for checking input equality when the two parties do not share the same hash function.
In recent years, the number-theoretic transform (NTT) has become increasingly common in cryptography, in part due to multiple lattice-based cryptographic schemes being selected for standardization during the NIST PQC competition. Indeed, polynomial multiplications are one of the most computing intensive operations in these schemes and the NTT is crucial in decreasing the performance cost. The NTT also appears in other areas such as fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKP) which are increasingly used in privacy-preserving applications. In this paper, we show how to formally specify the NTT in the Rocq proof assistant, and how we used this specification to automatically derive formally verified implementations of both complete and incomplete NTTs for multiple cryptographic schemes.
The ongoing transition to post-quantum cryptography has highlighted the need for digital signature schemes offering diverse performance and security trade-offs. Among the candidates in NIST’s ongoing post-quantum signature standardisation process is FAEST, a scheme built upon the Vector Oblivious Linear Evaluation in-the-Head (VOLEitH) paradigm introduced in 2023. VOLEitH enables efficient zero-knowledge proofs with competitive signature sizes under conservative assumptions, allowing FAEST to rely primarily on the one-wayness of the Advanced Encryption Standard (AES). Despite their promising efficiency, VOLEitH-based signature schemes have remained relatively unexplored from a physical security perspective. In this paper, we present the first side-channel security evaluation. Specifically, we demonstrate two single-trace, deep learning-assisted power analysis attacks on the masked implementation of FAEST by Aranha, Degn, Eilath, Nielsen, and Scholl. These attacks exploit leakage from witness bits and VOLE tag computations, recovering the full secret key with success probability above 0.99 from a single signature on an ARM Cortex-M4 processor. We further analyse how the VOLEitH construction enables profiling of VOLE tags without knowledge of the secret key and how even partial leakage of these tags compromises security. Finally, we discuss practical countermeasures to mitigate such leakages and strengthen the physical resilience of VOLEitH-based signature implementations.
Address verification and spend limit checks in card and instant payment systems expose cardholder ZIP codes and velocity histories to gateways and intermediaries, which increases the privacy impact of breaches. At the same time, issuers rely on these checks to control fraud within strict two to three hundred millisecond authorization budgets. This paper presents ZK-AVS, a design that replaces plaintext AVS and spend limit evaluation with zero knowledge proofs produced on the customer device and verified at the payment gateway. The issuer stores commitments to the cardholder ZIP and per window spend counters, and the device proves that its ZIP matches the committed value and that the proposed transaction keeps cumulative spend within the configured limit, without revealing the underlying values. We instantiate a synthetic workload of fifty thousand transactions and show that AVS mismatch and limit pressure carry useful fraud signal that can be exposed as proof outcomes. The design is structured to fit within sub three hundred millisecond budgets on commodity devices, while removing direct exposure of address and spend history data at the gateway and keeping changes largely at endpoints.