Margherita Cozzolino, Stephan Krenn, Thomas LorĂŒnser
While QKD ensures information-theoretic security at the link level, real-world deployments depend on trusted repeaters, creating potential vulnerabilities. In this paper, we thus introduce a topology-hiding connectivity assurance protocol to enhance trust in quantum key distribution (QKD) network infrastructures. Our protocol allows network providers to jointly prove the existence of a secure connection between endpoints without revealing internal topology details. By extending graph-signature techniques to support multi-graphs and hidden endpoints, we enable zero-knowledge proofs of connectivity that ensure both soundness and topology hiding. We further discuss how our approach can certify, e.g., multiple disjoint paths, supporting multi-path QKD scenarios. This work bridges cryptographic assurance methods with the operational requirements of QKD networks, promoting verifiable and privacy-preserving inter-network connectivity.
This paper describes a zero-knowledge proof system that enables verification of password policy compliance within an asymmetric password-authenticated key exchange (aPAKE) protocol specifically OPAQUE (RFC 9807) without revealing the password to the server. The system is built on a composable sub-circuit architecture: independent verification gadgets are combined into a single zero-knowledge proof, each gadget accepting portions of the private witness and producing public instance values, enabling the server to verify multiple password properties in one proof verification. Four gadgets are disclosed: (1) a Policy Engine for character class verification via lookup tables, (2) a History Nullifier for password inequality proof via squared-difference accumulation, (3) an OPAQUE Binder for cryptographic binding to the aPAKE registration element via hash-to-curve and elliptic curve scalar multiplication, and (4) a Breach Detector for offline breached-password detection via Bloom filter non-membership proof using algebraic hashing. The composable architecture permits addition of further gadgets without modifying existing ones, each extending the public instance vector.
Threshold transactions in Bitcoin is an effective solution for vulnerability of wallets to the loss or compromise of secret keys. It also enhances the applicability of Bitcoin to include use-cases that require partitioning the trust among a set of parties. Currently, the threshold transactions on Bitcoin expose the actual signers within the group of participants. This poses a threat of wallet hacks or theft targeting these signers. To address this issue of privacy, we propose a novel protocol to create threshold transaction using a combination of on-chain locking and off-chain proof of knowledge. As Bitcoin currently does not support verification of zero-knowledge schemes, the proposed protocol uses a Trusted Third Party ( TTP ) to verify the proofs off-chain. The trust on the third party is only limited to its service of signing on behalf of the users. The main contribution is the development and applicability of a m-out-of-N proof of partial knowledge that maintains the privacy of the signers both on-chain from the transaction verifiers and off-chain from the TTP and other signers as well. The protocol leverages Taprootâs spending path flexibility to incorporate dual spending capabilities and employs off-chain zero knowledge ÎŁ-protocols to prove knowledge of private keys without disclosing their associated public keys. Experimental analysis demonstrates improved scalability and privacy than the mainstream threshold signature schemes for Bitcoin. A formal analysis demonstrates and establishes the security goals of the proposed mechanism.
Federated unlearning enables clients to withdraw their contributions from a global model.However, enabling clients to verify whether the server has honestly and effectively removed their contributions remains a critical challenge. To address this aspect, which has been largely overlooked in existing literature, a verification model based on zero-knowledge proofs was constructed, and a comprehensive framework for verifiable federated unlearning was proposed. Combined with a dynamically updated Merkle tree structure, a novel verifiable federated unlearning scheme was presented characterized by its zero-knowledge property. This allows for the efficient generation of cryptographic proofs for server unlearning operations while rigorously protecting the data privacy of other clients. We evaluate the effectiveness and computational overhead of the proposed scheme. Comparative experiments with Rivest-Shamir-Adleman (RSA) accumulator-based and Hash chain-based schemes demonstrate that, when the model parameter size reaches the order of <inline-formula><alternatives><math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><msup><mrow><mn mathvariant="normal">10</mn></mrow><mrow><mn mathvariant="normal">5</mn></mrow></msup></math><graphic specific-use="big" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="alternativeImage/B6D6E598-14B1-468e-9A32-73199F9CD69E-M002.jpg"><?fx-imagestate width="4.23333359" height="2.53999996"?></graphic><graphic specific-use="small" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="alternativeImage/B6D6E598-14B1-468e-9A32-73199F9CD69E-M002c.jpg"><?fx-imagestate width="4.23333359" height="2.53999996"?></graphic></alternatives></inline-formula>, the proposed scheme improves proof generation speed by approximately two orders of magnitude and verification speed by 13.2 times compared to the RSA-based scheme. Furthermore, it effectively avoids the scalability bottleneck of data linear growth in verification overhead inherent in Hash chain-based schemes.
Abstract With the increasing reliance on cloud services, establishing secure and reliable authentication for terminal devices to remotely access and control data has become a critical challenge. Existing solutions often suffer from limitations such as concentrated computational load, privacy infringements, and dependence on centralized architectures that introduce single points of failure (SPOF). To address these issues, this paper proposes DTAP, a blockchain-based dual-terminal collaborative anonymous authentication protocol. DTAP introduces a novel architecture that splits the user terminal into a U-Shield and a smartphone: the U-Shield securely hosts the master key offline, providing a robust security anchor, while the smartphone leverages BBS+ signatures and zero-knowledge proofs to achieve privacy-preserving authentication and Fine-Grained Access Control (FGAC). Furthermore, the protocol employs blockchain technology to eliminate SPOF, with smart contracts ensuring tamper-proof logging and transactional transparency. Security analysis confirms that the protocol meets the required security properties. Performance evaluation shows that DTAP maintains competitive computational and communication efficiency despite its enhanced functionality, and its deployment on the Ethereum testnet demonstrates practical feasibility.
Traditional digital card games rely on centralized servers, introducing catastrophic single points of failure, while decentralized Web3 alternatives fail to achieve real-time viability due to prohibitive block latency. This paper introduces Panoptes, a highly optimized, hybrid Zero-Trust cryptographic engine that enforces microsecond-latency decentralized consensus for the CoronaPoker peer-to-peer network. Assuming a strict Ring-0 adversary model, Panoptes treats the host operating system and the Java Virtual Machine (JVM) as fundamentally compromised. We detail a bifurcated architecture utilizing a hardened native airgap that leverages OS-level stealth allocators to process ciphertexts without leaving plaintext residue in the managed heap. To mitigate OS-level memory scrapers and hardware-based Direct Memory Access (DMA) attacks, Panoptes implements a multiplexed decoy memory topology (The Vault). It is secured by strict virtual page guarding against software introspection, and heavily relies on offline decryption with immediate sub-millisecond zeroization to temporally starve asynchronous hardware-level carving. The protocol entirely replaces traditional commutative encryption with the deterministic Hand Commitment Megapacket, a flat-buffer payload leveraging X25519 KEM, Additive Secret Sharing, and ChaCha20-Poly1305 to ensure Byzantine fault tolerance without majority voting. We present formal implementations of our micro-architectural defenses, including Mixed Boolean-Arithmetic (MBA) for constant-time execution, direct cross-platform syscalls bypassing libc, OS-level DACL lockdowns, PEB cloaking, and asynchronous SipHash-2-4 binary attestation. Furthermore, we introduce a multithreaded Deadman Switch to detect CPU cycle drift via RDTSC. Evaluated under an exhaustive 42-point "Total Siege" adversarial framework, the engine demonstrates unparalleled resilience against hardware breakpoints, kernel introspection, inline hooking, and temporal drift attacks.
Cross-domain data exchange is an important technical approach for realizing the value of data assets. However, lacking a single trusted root CA across domains, cross-domain schemes often encounter difficulties in authentication, controlled data flow, and fine-grained authorization. We propose a cross-domain data sharing scheme that uses decentralized identifiers and threshold proxy re-encryption. This scheme adopts the intra-domain leader node to verify the user identity, and the inter-domain multi-agent nodes collaborate in a threshold manner to handle cross-domain registration requests and re-encryption requests. Through threshold cooperation, the problem of single point of failure is effectively solved. The hash value of cross-domain registration information is stored on the blockchain, leveraging the immutable and traceable characteristics of blockchain to achieve trusted cross-domain data sharing. In addition, we introduce a ciphertext version tag to enable fast updates of re-encryption keys and use zero-knowledge proofs to verify re-encrypted ciphertext correctness. The security analysis indicates that our scheme has IND-CCA2 security under the DBDH assumption and can effectively resist collusion attacks. Performance analysis shows that our scheme is efficient, and can better meet the needs of cross-domain data sharing.
Muhammad Ahmed, Adnan Ahmad, Furkh Zeshan, Sheeraz Akram
Blockchain-based systems increasingly require authentication mechanisms that simultaneously preserve user privacy, support accountability, and enable efficient credential revocation. However, most existing anonymous authentication schemes rely on pairing-based cryptography which introduce high computational overhead and limit deploy ability on widely adopted blockchain platforms such as Ethereum. This paper presents BAAR, a Blockchain-based Anonymous and Revocable authentication framework designed entirely within the discrete logarithm setting over the secp256k1 elliptic curve. BAAR integrates Pedersen vector commitments, Schnorr-based zero-knowledge proofs, and a Merkle-tree-based dynamic accumulator to support anonymous and unlinkable authentication with selective attribute disclosure and public, auditable revocation. Authentication and proof verification are performed off-chain, while the blockchain maintains only a compact revocation state, significantly reducing on-chain computation and gas costs. A formal security analysis demonstrates unforgeability, unlinkability, attribute privacy, and revocation soundness under standard cryptographic assumptions in the random oracle model. A prototype implementation on Ethereum confirms that BAAR achieves low gas consumption, logarithmic-time revocation, and scalable performance with respect to both the number of users and attributes. These results indicate that BAAR provides a practical balance between strong privacy guarantees and deploy ability, making it suitable for real-world blockchain-based identity and access-control systems.
The proliferation of Internet of Things (IoT) devices creates unprecedented security, privacy, and transparency challenges in distributed systems. Traditional encryption-based approaches provide privacy but impose significant computational overhead, storage bloat, and key management complexity. This paper presents CIPHER-IoT, a blockchain-based framework that integrates Zero-Knowledge Proofs (ZKPs) with Hyperledger Fabric for privacy-preserving IoT data management. Unlike encryption-based approaches that store encrypted data on-chain, CIPHER-IoT utilises Groth16 zk-SNARKs to generate cryptographic proofs of data validity while storing only commitments on the blockchain, achieving stronger privacy guarantees with lower storage overhead. The framework employs Ed25519 for lightweight digital signatures and implements comprehensive chaincode for ZKP verification, commitment uniqueness checking, and access control enforcement. CIPHER-IoT targets gateway/edge IoT deployments with moderate computational capacity (ARM processors 500 MHz+) rather than ultra-constrained sensors. We evaluate CIPHER-IoT against two baseline systems, SPAS (homomorphic encryption-based) and SPAS-H (AES encryption with Hyperledger Fabric), using realistic simulation with 50â500 devices and transaction rates of 10â75 TPS. Experimental results demonstrate superior privacy (98% confidentiality vs. 80â95% for encryption-based approaches) alongside competitive performance: read latency improves 37% (p < 0.001), throughput increases 14.6% (p < 0.001), memory reduces 21.4%, network bandwidth saves 47%, and disk I/O reduces 37.8%. The system maintains zero data loss under failure scenarios and scales linearly to 500 devices with minimal degradation (9.9%). CIPHER-IoT demonstrates that verification-based privacy mechanisms can achieve stronger privacy and better performance than transformation-based approaches in distributed validation contexts, particularly suitable for enterprise IoT deployments requiring coordinated privacy-preserving infrastructure.
Cross-chain bridges represent one of the most critical yet vulnerable components of blockchain infrastructure, with over $2.5 billion lost to bridge exploits between 2022-2023 alone. MERIDIAN LINK introduces an architecture combining Light Protocol's ZK Compression on Solana with GrotH16 zero-knowledge proofs for verification on EVM chains, reducing trust assumptions compared to signature-based bridges while acknowledging explicit trade-offs. Key Properties: Cost reduction: 95%+ savings on Solana storage via compressed accounts (~15,000vs ~1,600,000 lamports per deposit record) Verification: GroTH16 proofs (~100-bit security on BN254) replace multisig attes-tation for withdrawal authorization Latency: ~20-25 seconds end-to-end (competitive with intent-based bridges) Replay protection: Poseidon-based nullifiers with on-chain tracking Explicit Limitations: Throughput: ~12-20 withdrawals per minute per direction (sequential IMT updates) EVM costs: Withdrawal verification costs ~$4-6 at 30 gwei, dominating total transfer cost Trust assumptions: GroTH16 trusted setup, Light Protocol implementation, Photon indexer availability, relayer liveness The protocol shifts the trust model from "honest majority of signers" to "cryptographic soundness plus infrastructure liveness." A compromised relayer cannot forge proofs or double-spend, but can censor transactions or extract MEV through reordering.
The integrity of distributed healthcare databases is continuously threatened by unauthorized modifications, hardware faults, software vulnerabilities, and increasingly sophisticated cyberattacks. Traditional relational and NoSQL database systems rely on centralized access-control mechanisms and periodic audit logs that cannot provide cryptographic proof of unaltered history or real-time anomaly detection. This paper presents ChainGuard, a novel middleware framework that integrates Ethereum-based smart contracts, a network of IoT integrity-sensing nodes, and an AI-powered anomaly classifier to provide end-to-end, tamper-evident integrity assurance for distributed healthcare information systems. ChainGuard records SHA-256 hash digests of critical database state snapshots onto a permissioned Ethereum ledger, while a constellation of lightweight IoT agents embedded at database server nodes continuously monitors system-level indicatorsâI/O throughput, memory bus activity, and cryptographic nonce validationâat ten-second intervals. Deviations from baseline behavior trigger smart-contract-enforced quarantine procedures that freeze suspect transactions and emit verifiable incident records onto the immutable ledger. A Random Forest classifier trained on 12,000 synthetic database-event logs achieves 96.4% accuracy in discriminating legitimate bulk insertions from covert data-tampering attempts. Evaluation across three clinical deployment scenarios demonstrates that ChainGuard reduces mean time to tamper detection from 47 minutes (baseline centralized audit) to 38 seconds, with a false-positive rate of 1.7%. The framework is deployable on existing PostgreSQL and MongoDB infrastructure without schema modification, making it an immediately practicable path toward regulatory compliance with HIPAA, GDPR, and the forthcoming NIS2 Directive.
Oliver Aleksander Larsen, Rasmus Stenbak Larsen, Mahyar Tourchi Moghaddam
Today's internet concentrates identity, payments, communication, and content hosting under a small number of corporate intermediaries, creating single points of failure, enabling censorship, and extracting economic rent from participants. We present BitSov, an architectural framework for sovereign internet infrastructure that composes existing decentralized technologies (Bitcoin, Lightning Network, decentralized storage, federated messaging, and mesh connectivity) into a unified, eight-layer protocol stack anchored to Bitcoin's base layer. The framework introduces three architectural patterns: (1) payment-gated messaging, where every transmitted message requires cryptographic proof of a Bitcoin payment, deterring spam through economic incentives rather than moderation; (2) timechain-locked contracts, which anchor subscriptions and licenses to Bitcoin block height (the timechain) rather than calendar dates; and (3) a self-sustaining economic flywheel that converts service revenue into infrastructure growth. A dual settlement model supports both on-chain transactions for permanence and auditability and Lightning micropayments for high-frequency messaging. As a position paper, we analyze the quality attributes, discuss open challenges, and propose a research agenda for empirical validation.
The growing adoption of the Electronic Health Records (EHR) has revolutionized healthcare information management. However, seamless and secure interoperability between different healthcare organizations continues to be a hard challenge. Data silos, centralized trust model, and lack of scalability are common impairments of traditional systems in care delivery which limit âpatient centricâ way of care delivery. While blockchain technology offers decentralized trust and immutability, current solutions tend to be closed on a single blockchain platform, and thus not able to provide cross network interoperability and accessing data. To address this gap, this research introduces a Cross Chain EHR Sharing Framework that may be leveraged for the secure, bi-directional synchronization of EHR between Hyperledger Fabric (private blockchain) and Ethereum Sepolia Testnet (public blockchain) via decentralized storage by IPFS with AES 256 encryption. To facilitate interoperability the research introduces a smart middleware layer that autonomously monitors the blockchain events, processes encrypted Content Identifier (CID)s, enforces real time cross chain consistency and smart contract-based access control. The experimental evaluation shows that proposed framework achieves low synchronization times (< 195 ms), efficient blockchain operations with low gas and latency costs, small encryption overhead (< 4â5 KB), robust file storage and retrieval through IPFS. It also provides scalability, security and real-world applicability for the cross-chain healthcare interoperability.
Ryan Babbush, Adam Zalcman, Craig Gidney, Michael Broughton · 9 authors
This whitepaper seeks to elucidate implications that the capabilities of developing quantum architectures have on blockchain vulnerabilities and mitigation strategies. First, we provide new resource estimates for breaking the 256-bit Elliptic Curve Discrete Logarithm Problem, the core of modern blockchain cryptography. We demonstrate that Shor's algorithm for this problem can execute with either <1200 logical qubits and <90 million Toffoli gates or <1450 logical qubits and <70 million Toffoli gates. In the interest of responsible disclosure, we use a zero-knowledge proof to validate these results without disclosing attack vectors. On superconducting architectures with 1e-3 physical error rates and planar connectivity, those circuits can execute in minutes using fewer than half a million physical qubits. We introduce a critical distinction between fast-clock (such as superconducting and photonic) and slow-clock (such as neutral atom and ion trap) architectures. Our analysis reveals that the first fast-clock CRQCs would enable on-spend attacks on public mempool transactions of some cryptocurrencies. We survey major cryptocurrency vulnerabilities through this lens, identifying systemic risks associated with advanced features in some blockchains such as smart contracts, Proof-of-Stake consensus, and Data Availability Sampling, as well as the enduring concern of abandoned assets. We argue that technical solutions would benefit from accompanying public policy and discuss various frameworks of digital salvage to regulate the recovery or destruction of dormant assets while preventing adversarial seizure. We also discuss implications for other digital assets and tokenization as well as challenges and successful examples of the ongoing transition to Post-Quantum Cryptography (PQC). Finally, we urge all vulnerable cryptocurrency communities to join the ongoing migration to PQC without delay.
Blockchain-based electronic voting systems that use zero-knowledge proofs (ZKPs) have been proposed as good candidates to provide both transparency and privacy of ballots. However, a fundamental challenge remains unmet in all existing schemes: the secure generation and protection of the voter's cryptographic secret key.In this paper, HME-KG (Hybrid Multi-Source Entropy Key Generation) is presented, a new credential derivation method which utilizes a cryptographically secure random salt, the national identity number of the voter and a per-device Client Device Secret (CDS) to derive a deterministic, brute-force-resistant secret key. HME-KG is integrated into BAVS-ZK, a complete anonymous blockchain voting framework employing AES-256-GCM encrypted credential storage, a Circom-based Groth16 zk-SNARK voting circuit, and on-chain nullifier verification via Ethereum Sepolia smart contracts. Security analysis demonstrates that HME-KG achieves voter determinism, cross-voter uniqueness, single-source failure resistance, and collision resistance under the security assumptions of SHA-256. Experimental evaluation on a 10,000-voter simulation confirms a 0.9998 scalability coefficient, 1.2-second proof generation, and 306,720 gas per voteâa 38.6% reduction compared to the Open Vote Network baseline. To the extent of current literature, BAVS-ZK is the first blockchain e-voting system to provide a complete, formally specified, and experimentally validated voter credential derivation and protection scheme.
Wireless medical sensor networks (WMSNs) enable continuous patient monitoring by transmitting sensitive physiological data over open wireless links. Given the resource-constrained nature and large-scale deployment of such networks, authentication mechanisms must be both lightweight and privacy-preserving. Moreover, due to the frequent turnover of patients and devices in hospital environments, timely member revocation is crucial to prevent discharged or compromised entities from injecting forged reports that could mislead medical diagnosis. Although existing pairing-free certificateless aggregate authentication schemes are efficient, they often suffer from critical security and privacy vulnerabilities. Recently, an efficient certificateless authentication scheme with revocation has been proposed. However, our analysis reveals that the scheme presents the following security vulnerabilities: (i) member witnesses can be recovered from public information, (ii) revocation checks can be bypassed via identity grafting attack, and (iii) user identities can be linked due to the long-term use of static pseudonyms. To address these issues, we propose a security-enhanced certificateless aggregate authentication protocol with revocation for WMSNs. Our design enforces strong identity-membership binding to resist grafting attacks, employs a non-interactive zero-knowledge membership proof to preserve witness secrecy, and adopts dynamic pseudonym rotation to achieve unlinkability. We provide formal security proofs and comprehensive performance comparisons. The results indicate that, at the same security level, our protocol achieves more efficient signature verification while maintaining communication overhead comparable to existing schemes. In addition, the overhead introduced by our revocation mechanism remains constant, making it well suited for large-scale WMSNs deployments with frequent membership changes.
Federated Learning (FL) is an approach that allows numerous users to train a single machine learning model with the oversight of a central server, and with their training data stored locally on their devices. The approach is relevant in alleviating the risks associated with violations in data privacy. It is a process by which a pool of clients collaborates towards solving machine learning problems, with a central coordinator being the one who coordinates the entire process. The paper will review the latest advances in privacy-preserving federated learning and discuss it in the context of machine learning. It assesses privacy-related solutions, which are already in existence, such as secure aggregation, meta-learning, blockchain technology, decentralized training, searchable encryption, and data privacy mechanisms and zero-knowledge proofs. Federated learning (FL) is an emerging technology that can be used in the realm of the intelligence of the Internet of Things. However, the information that is model-related can be shared in FL and reveal the sensitive data of the participants. In this regard, we propose a new privacy-preserving FL framework, which is founded on a new chained secure multiparty computing technique, which we call chain-PPFL. The scheme we are proposing is based mostly on two mechanisms: 1) a single-masking mechanism, which protects the information that is exchanged between participants in a serial chain frame and 2) a chained-communication mechanism, which allows the masked information to be communicated between participants in a serial chain frame. We run large-scale experiments with respect to simulation by comparing the training accuracy and the leak defence to other state-of-the-art schemes with two publicly available data sets (MNIST and CIFAR-100). We established data sample distributions (IID and NonIID), and training models (CNN, MLP and L-BFGS) in our experiments. The experiment results show that the chain-PPFL scheme can offer a realistic privacy preservation (which is the same as the various privacy with Ï” to near zero) to FL at the cost of communication, and without compromising the accuracy and convergence rate of the training model.
Authorization tokens in distributed systems are typically context-free: a cryptographically valid token carries no binding to the specific transaction for which it was issued. This enables reuse and cross-context presentation attacks that are undetectable at the cryptographic layer. In regulated financial infrastructure, cross-border payments, and autonomous agent systems, transaction-scoped enforcement is a hard requirement that existing standards leave unaddressed. We introduce the first formal security model for policy-bound transaction tokens. We define the syntax of a policy-bound transaction token scheme over a formal transaction context space and introduce three game-based security notions: transaction binding (TB), which simultaneously resists forgery and cross-context reuse; existential unforgeability under chosen-context attack (EUF-CCA); and unlinkability (UNL). We prove that TB strictly implies EUF-CCA, establish a formal separation between TB and UNL, and identify the inherent tension between unlinkability and auditability. We construct a scheme parameterized by any EUF-CMA-secure signature scheme and a random oracle, and prove that it achieves transaction binding security with a tight reduction requiring no rewinding. We then address the complementary privacy problem by formalizing zero-knowledge compliance privacy (ZK-CP) and constructing an enhanced scheme that augments transaction-binding tokens with a non-interactive zero-knowledge proof of policy compliance. We prove that the enhanced scheme simultaneously achieves TB security and ZK-CP, and show how it integrates with decentralized identity (DID) systems to enable fully privacy-preserving authorization where the verifier learns only whether compliance is satisfied. We give a concrete instantiation using Ed25519 and SHA-512, derive bit-security parameters, analyze performance costs, and discuss deployment considerations including regulatory alignment with PSD2, MiCA, DORA, the GENIUS Act, SEC token taxonomy, and FinCEN BSA requirements.
This paper systematically reviews the research foundation, core technologies, and practical applications of cryptography in the blockchain field. Algorithms, and data immutability relies on cryptographic hash functions and Merkle tree structure; the balance between transparency and privacy in block chain relies on the encryption technique of zero-knowledge proofs, ring signature, homomorphic encryption. Therefore, every part of block chain is based on cryptography; without the mathematical guarantee of cryptography, the trust decentralized by block chain is meaningless. The security of block chain mainly relies on the encryption techniques such as hash functions, digital signatures and encryption algorithms, and traditional cryptographic methods will have vulnerabilities when facing quantum computing, because quantum computer may be used to break currently commonly used algorithms such as RSA, ECC eventually. This âsecurity paradox" requires us to pay more attention to block chain technologies, because block chain technology needs to advance in tandem with cryptography. Traditional blockchain technologies canât be used indefinitely. Against this background, researching block chain ïŒbased crypto is of great theoretical significance and practical value: on the one hand, researching on new cryptographic methods applicable to block chain can extend the area of cryptosystems and give people a new way of solving the security problems in block chain; on the other hand, we should not neglect the possibility of breaking the block chain by combining quantum computing with cryptanalysis research.
Proof-of-work (PoW) blockchains expend energy solely for network security. Proof of Useful Work (PoUW) aims to reclaim this cost, but stateful proving (e.g., multi-phase STARKs) breaks the memoryless property required for Nakamoto consensus. ZK-SPoW (Zero-Knowledge Symbiotic Proof of Work) inverts the relationship: instead of making PoW useful, useful STARK Merkle hashing naturally produces PoW tickets as a cryptographic byproduct of every Poseidon2 permutation. Under the pseudorandom permutation (PRP) assumption, each permutation is computationally indistinguishable from an independent Bernoulli trial at nanosecond granularity â restoring computational memorylessness at the permutation level without sacrificing useful computation. We instantiate with Width-24 Poseidon2 over M31: each permutation simultaneously produces a Merkle parent (ZK output) and three PoW tickets. Usefulness is not protocol-enforced but market-driven â miners select which ZK proofs to generate or fall back to Pure PoW, guided by proof demand. Statistical validation via the full NIST SP 800-22 test suite (15/15 tests pass) confirms the pseudorandom quality of the Poseidon2-based mining output.
Human-friendly identifiers such as email addresses and phone numbers are convenient payment targets, but direct mappings from identifiers to blockchain addresses make balances and transaction histories enumerable by anyone who knows the identifier. We present HFI-Pay, a relay-assisted protocol for privacy-preserving identifier-routed cryptocurrency payments. The relay resolves the identifier off-chain and registers only a random intent identifier, a per-intent blinded binding rho_i, and the quoted payment tuple on-chain; no identifier or reusable recipient tag is published before claim. In a verified-quote deployment, the sender verifies an attested quote proving that rho_i was derived from the same hidden binding handle as the recipient's attested binding-key commitment, preventing relay-side recipient substitution before funding. Claims are authorized by a zero-knowledge proof, instantiated through ZK-ACE, that the claimant controls the deterministic identity whose epoch-scoped handle opens the blinded binding and authorizes release of the quoted asset and amount to a chosen destination. We define observer-model games for enumeration resistance and pre-claim unlinkability, state the composition needed for post-quote claim correctness, and characterize relay compromise and post-claim linkability. Keywords: identifier-based payment, privacy-preserving, verifiable quote, blinded claim binding, zero-knowledge authorization
Tangible Encryption is a cryptographic framework that replaces the âsecret zeroâ bootstrap problem in secrets management with a verifiable, identity-based trust model. Instead of requiring an antecedent credential to access protected secrets, this approach binds access control to ownership of a persistent cryptographic token (e.g., an NFT), enabling authentication through proof of ownership rather than shared knowledge. This work formalizes the use of non-fungible tokens as ownable roots of trust, where token ownership encodes identity, access rights, and provenance on a distributed ledger. A deterministic key derivation model is introduced, allowing secrets to be encrypted and decrypted without transmitting or storing a traditional master secret. Verification is performed via cryptographic signatures and on-chain state checks, eliminating circular trust dependencies inherent in systems such as Vault, SOPS, and cloud KMS. The framework is evaluated in the context of AI systems, including model provenance, secure dataset access, and autonomous agent authentication across organizational boundaries. Security considerations such as key compromise, revocation, and ledger integrity are analyzed, alongside implementation tradeoffs between public and permissioned ledgers. Tangible Encryption establishes a portable, verifiable trust anchor that operates independently of any single platform or identity provider, unifying identity, access control, and auditability into a single cryptographic primitive.
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Cryptography and Data Security
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security