Communication and networked systems rely heavily on cryptographic digital signatures to ensure message authenticity, integrity, and non-repudiation. However, rapid advancements in quantum computing and artificial intelligence (AI) have expanded the attack surface, posing significant threats to conventional public-key schemes such as RSA, DSA, and ECDSA. Quantum algorithms undermine their underlying hardness assumptions, while AI-driven techniques enable traffic analysis, side-channel inference, and behavioral pattern recognition. This review presents a structured analytical assessment of post-quantum signature schemes and privacy-preserving authentication mechanisms to address these dual threats. It evaluates lattice-based, hash-based, and zero-knowledge proof-based signatures, as well as anonymity-enhancing schemes such as ring and group signatures. A unified analytical framework is introduced to map cryptographic schemes to quantum and AI-assisted threat models, based on parameters such as security strength, anonymity, efficiency, and applicability. The analysis shows that lattice- and hash-based schemes provide strong quantum resistance, while privacy-preserving mechanisms enhance anonymity but introduce performance trade-offs. It also identifies a gap in integrating post-quantum cryptography with AI-resilient privacy mechanisms. The findings highlight the need for unified, future-ready cryptographic designs.
Modern representative democracies are increasingly vulnerable to systemic structural failure modes, including special-interest capture, asymmetric foreign intelligence leverage, and informational noise saturation (astroturfing/botnets). This paper introduces the Cryptographic Agora, a novel institutional framework that transitions governance from representative mediation to a scientifically audited, direct epistocracy. The model synthesizes three core architectural components: (1) state-verified biometric identity mapping coupled with Zero-Knowledge Proofs (ZKPs) to guarantee non-traceable, un-hackable civic participation; (2) a dynamic reputation engine utilizing Quadratic Weighting to mitigate the concentration of charismatic authority; and (3) a double-blind, retrospective peer-review protocol modeled on the scientific method to vet policy proposals. We evaluate the structural resilience of this framework against traditional threats, detailing its capacity to achieve a self-correcting equilibrium while maintaining individual voter safety and systemic legitimacy.
Proof-of-Work blockchains secure consensus through hash puzzles, producing no external value. In this research, we propose a decentralized AI economy where nodes are rewarded for useful machine-learning work, i.e., inference and training, instead of ineffective hashing method. Our proposed three-layer architecture separates compute, validation, and economic coordination. We formalize it via a $(θ_c, θ_w, W)$-closed-loop token economy and derive a sufficient-stake condition for honest participation. While existing Grover's algorithm provides only a quadratic speedup against hash puzzles, it does not accelerate ML-native linear algebra. On the other hand, Shor's algorithm threatens classical blockchain signatures. Post-quantum migration to lattice-based and hash-based standards can address the signature layer. Therefore, useful-work consensus thus offers both economic and quantum-security advantages over classical proof-of-work.
Local AI inference for browser tasks—including vision-language processing, speech recognition, and neural translation—requires significant computational resources that may exceed the capabilities of low-power devices such as smartphones, tablets, and older laptops. This paper presents the design of a distributed GPU compute sharing system for the Kathon cryptographic browser that enables peer-to-peer AI inference acceleration across trusted devices using libp2p networking. The system partitions neural network inference workloads across participating peers using tensor parallelism, with encrypted communication channels, verifiable computation proofs, and incentive mechanisms based on the .aioss cryptographic ledger. We address key technical challenges: heterogeneous device discovery with capability advertisement, dynamic workload partitioning for variable peer availability, encrypted inference that prevents input reconstruction, and fault tolerance through redundant computation. Simulated benchmarks across a 16-peer testbed demonstrate 3.8x speedup for Whisper transcription and 4.2x speedup for Qwen 2.5 VL inference on low-power client devices. A security analysis confirms that encrypted inference provides semantic security against honest-but-curious peers. The system enables Kathon to deliver AI features on devices that lack the local compute capacity for real-time inference. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores browser engine, privacy in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a comprehensive analysis of privacy-preserving authentication mechanisms within the MF+SO sovereign identity vault, focusing on the protocol's implementation of zero-knowledge identity proofs, anonymous credentials, blind signatures, and data minimization techniques. Traditional authentication protocols require the user to disclose their identity to each service provider, creating a centralized record of the user's activities across services. MF+SO's privacy architecture inverts this model: users authenticate to services without revealing their MF+SO identifier, using cryptographic techniques that provide the verifier with assurance of the user's authorization status while revealing minimal information about the user's identity. We examine three canonical privacy-preserving authentication mechanisms implemented in MF+SO: (1) zero-knowledge identity proofs using the Groth16 zk-SNARK construction, enabling users to prove possession of valid credentials without revealing which credentials they hold; (2) anonymous credentials based on the Camenisch-Lysyanskaya (CL) signature scheme, providing multi-show unlinkability where the same credential can be presented multiple times without the presentations being correlatable; and (3) blind signature-based tokens for email cloaking, where the MF+SO service issues a blind signature on a user's email address for use with third-party services without learning the email address. The paper provides a formal security analysis of the unlinkability guarantees of each mechanism, proving that under the decisional Diffie-Hellman (DDH) assumption, CL-based anonymous credential presentations are computationally unlinkable. We present benchmark data for each mechanism on mobile platforms: CL credential issuance (120 ms), CL credential presentation (85 ms), blind RSA signature issuance (45 ms), and zk-SNARK-based verification (2.3 ms). The implementation details include the MF+SO privacy layer architecture, the credential ... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Organizations operating multiple AI systems generate independent cryptographic ledgers that may need mutual verification, cross-referencing, or consolidated audit for enterprise-wide compliance reporting. Cross-chain notarization provides cryptographic evidence that a ledger's state is acknowledged by another independent ledger, enabling distributed audit verification without central coordination. This paper presents the design and analysis of the AIOSS cross-chain notarization protocol, which anchors the hash chain head of one ledger into another by inserting a notarization entry containing the cross-chain proof. We define three notarization modes: unilateral (ledger A notarizes ledger B's state), bilateral (mutual notarization between A and B), and supervised (third-party notarizer with independent proof). The notarization proof comprises a Merkle inclusion proof of the source ledger's state proof within a notarization ledger entry, enabling verification by any party holding both ledger files. We analyze the security of cross-chain anchoring under the common prefix assumption, proving that notarization preserves the integrity of both ledgers. Performance benchmarks demonstrate that notarization completes in under 200 milliseconds for ledgers of up to 1 million entries. We further evaluate the notarization merge operation, which produces a unified ledger from multiple notarized ledgers with cross-reference integrity. The protocol supports regulatory requirements for multi-system audit consolidation under SOC2 reporting and GDPR Article 30 record-of-processing activities. --- Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores hash chain, cryptography in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a rigorous analysis of the hash chain auditability mechanism implemented within the MF+SO sovereign identity vault, specifically the `.aioss` hash chain data structure. The hash chain links successive vault state commitments through SHA3-256 cryptographic hashes, creating an immutable, tamper-evident log of all state transitions. Each link in the chain incorporates a parent_hash invariant that binds the current state to the entire prior history, a canonical JSON serialization of the vault state to ensure deterministic hashing across platforms, and an Ed25519 signature providing cryptographic proof of authenticity. We demonstrate that this construction achieves the forensic auditability properties first described by Haber and Stornetta (1991) for digital timestamping, extended to the identity management domain. The paper provides a formal mathematical model of the chain construction, analyzes the computational and storage costs of chain verification, presents a security proof for the tamper-detection properties under the random oracle model, and compares the MF+SO approach against alternative audit log constructions including Merkle trees, Certificate Transparency logs, and blockchain-based registries. The implementation leverages SHA3-256's sponge construction to eliminate length extension vulnerabilities that would compromise naive hash chain implementations. Empirical measurements demonstrate that chain verification for a typical user with 10,000 state transitions completes in under 200 milliseconds on modern mobile hardware. The paper concludes with an analysis of forward secrecy guarantees, key rotation impacts on chain continuity, and proposed extensions for zero-knowledge proofs of chain membership. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Privacy-preserving systems have traditionally faced a fundamental tradeoff between data utility and confidentiality. Selective Disclosure Credentials (SDCs) enable users to prove specific attributes without revealing underlying personal information, while Fully Homomorphic Encryption (FHE) enables arbitrary computation on encrypted data without exposing plaintext. Although both technologies address critical privacy challenges, they solve different problems and are rarely integrated into a unified architecture. This paper introduces the concept of Composable Privacy, a layered framework that combines selective disclosure credentials, zero-knowledge proofs, and fully homomorphic encryption into a cohesive privacy architecture. The framework separates privacy concerns into three functional layers: an authentication layer using selective disclosure and zero-knowledge proofs, a computation layer using homomorphic encryption for confidential processing, and a verification layer that provides cryptographic assurances of computation correctness. The paper examines the cryptographic foundations of BBS+ signatures, Coconut threshold credentials, lattice-based homomorphic encryption schemes, and post-quantum security considerations. It further evaluates the practical feasibility of the architecture through applications in decentralized finance, healthcare federated learning, confidential governance systems, and blockchain-based identity infrastructure. Performance trends, scalability challenges, interoperability requirements, and future hardware acceleration pathways are also analyzed. The proposed Composable Privacy framework demonstrates how selective disclosure and encrypted computation can be combined to create privacy-preserving digital systems that maintain verifiability, confidentiality, and regulatory compliance simultaneously. The work provides a conceptual foundation for next-generation privacy architectures in blockchain, decentralized identity, and distributed computing environments.
This paper presents a comprehensive analysis of zero-knowledge proof (ZKP) systems and their application to privacy-preserving identity management within the MF+SO sovereign identity vault. Zero-knowledge proofs, introduced by Goldwasser, Micali, and Rackoff (1985), enable a prover to convince a verifier of the truth of a statement without revealing any information beyond the statement's validity. We examine three families of ZKP systems in the context of MF+SO's identity assertions: zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge), zk-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge), and Bulletproofs. For each family, we analyze the setup assumptions (trusted setup vs. transparent), proof size, verification complexity, prover computation, and post-quantum security. The paper identifies three canonical use cases within MF+SO: (1) age verification without date of birth disclosure, where the user proves that their age exceeds a threshold without revealing their exact birth date; (2) credential possession proof, where the user proves they hold a valid credential for a resource without revealing which credential among a set they hold; and (3) membership in an allowlist without position disclosure, where the user proves their identifier appears in a list without revealing their position in the list. We present benchmark data for each use case using the Groth16 zk-SNARK (prover time: 1.2 seconds, proof size: 192 bytes, verification: 2.3 ms) and the STARK-based approach using the Winterfell library (prover time: 4.8 seconds, proof size: 48 KB, verification: 8.1 ms). The implementation complexity analysis demonstrates that zk-SNARKs require trusted setup ceremonies but provide the most compact proofs, while zk-STARKs eliminate the trusted setup requirement at the cost of larger proofs. The paper concludes with an analysis of the protocol integration requirements, including circuit compilation for the MF+SO identity predicate lang... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
You Wu, XinFeng Dong, Yongqiang Li, F Liu · 8 authors
Abstract With the development and practical application of technologies such as Fully Homomorphic Encryption (FHE), Secure Multi-Party Computation (MPC), and Zero-Knowledge Proof (ZK), it has become crucial to research the design and analysis of symmetric cryptographic primitives with low multiplicative complexity and depth. First, by using multiplication and addition over the finite field $$\mathbb {F}_{q}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:mi>q</mml:mi> </mml:msub> </mml:math> , where $$q$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>q</mml:mi> </mml:math> is either a prime number $$p$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> or $$2^{n}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:msup> </mml:math> , we proposed a non-linear function over $$\mathbb {F}_{q}^{4}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>F</mml:mi> <mml:mrow> <mml:mi>q</mml:mi> </mml:mrow> <mml:mn>4</mml:mn> </mml:msubsup> </mml:math> based on the generalized Feistel structure. This function features a multiplicative complexity of 4, a multiplicative depth of 2 and 8 additions, and its maximum differential/linear probability of the function is bounded by $$q^{-2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>q</mml:mi> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:math> . Then, we designed a family of HE-friendly block ciphers called DuX. We conduct a comprehensive security analysis of DuX within certain parameters against various cryptanalysis methods, including differential cryptanalysis, linear cryptanalysis, impossible differential cryptanalysis, zero-correlation linear cryptanalysis, integral analysis, related-key differential cryptanalysis, algebraic attacks, slide attacks, reflection attacks, and boomerang attacks. Our research indicates that DuX maintains a robust security margin against those attacks. Finally, based on the BGV scheme in HElib, we present a detailed homomorphic decryption implementation of the DuX instantiated with $$q = 2^{8}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>=</mml:mo> <mml:msup> <mml:mn>2</mml:mn> <mml:mn>8</mml:mn> </mml:msup> </mml:mrow> </mml:math> , $$2^{16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>2</mml:mn> <mml:mn>16</mml:mn> </mml:msup> </mml:math> and $$65537$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>65537</mml:mn> </mml:mrow> </mml:math> , respectively. The results show that, for the same block size, the throughput of the DuX-128 over $$\mathbb {F}_{2^{8}}^{16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>F</mml:mi> <mml:mrow> <mml:msup> <mml:mn>2</mml:mn> <mml:mn>8</mml:mn> </mml:msup> </mml:mrow> <mml:mn>16</mml:mn> </mml:msubsup> </mml:math> can reach approximately 14.95 times, 7.85 times and 20.76 times that of the AES-128, Low MC-128 and CHAGHRI, respectively. Compared with YuX-128, its throughput has increased approximately by 21.59%.
The division between traditional finance (TradFi) and decentralized finance (DeFi) continues tohinder seamless capital mobility across ecosystems. Real‑Time Payment Systems (RTPS) achievenear‑instant fiat settlements, yet bridging these assets into blockchain environments remainsdependent on fragmented, high‑latency, and centralized gateways. This gap limits the naturalstrengths of both worlds, especially speed and efficiency. Based on the publish/subscribe model, theEDSP protocol operates as a decentralized oracle system that allows for synchronization of stateupdates between two separate ledgers. This protocol will allow smart contracts to initiate fiatpayments and bank payment systems to trigger corresponding blockchain settlement actions. Themodel stresses cryptographic protections against oracle tampering through multi-party authenticationand zero-trust routing methodologies. A simulation of latency shows that an event-driven architectureis capable of resolving the deterministic nature of TradFi operations and the probabilistic aspect ofblockchain networks. Incorporating compliance events into the settlement process enables institutionsto meet their demands for regulatory and transparency obligations. This article sets a roadmap forfuture liquidity bridging models based on a secure, scalable, and compliant approach to bridgingecosystems. This article proves the value that event-driven models bring to the table in terms ofinterconnectivity and liquidity, which will allow institutional-level interactions to take place withinfiat and decentralized networks.
Abstract We present a post-quantum, cross-chain Aadhaar e-KYC system that decouples citizen identity from any single blockchain while preserving full quantum resistance. The system introduces did:pqie — a new W3C Decentralized Identifier (DID) method grounded in Ring Learning With Errors (Ring-LWE) cryptography (n = 512, q = 24593, = 4.0) — and demonstrates its application across three heterogeneous ledgers: Hyperledger Indy, Ethereum, and Polkadot. Upon government approval of a KYC submission, the system automatically issues a W3C Verifiable Credential anchored simultaneously on all three chains. Service access is gated by a Zero-Knowledge Proof (ZKP)-based token that proves credential validity without revealing any personally identifiable information. Selective disclosure via Merkle commitments allows citizens to reveal only required attributes. Our evaluation shows that the entire system — DID generation, multi-chain VC issuance, and ZKP token generation — operates within practical latency bounds while providing 256-bit post-quantum security. The did:pqie method has been submitted for registration with the W3C DID Methods Registry.
Dr. B. Indira Reddy, Naga Siva Jyothi Kompalli, Dr. Rohita yamaganti, CH Sai Saketh · 6 authors
The ongoing digital evolution in the healthcare sector has increased the demand for reliable and secure systems to manage medical records. Conventional centralized storage methods are vulnerable to security threats such as data breaches, unauthorized usage, and potential data alteration, which can compromise patient confidentiality and data integrity. To overcome these challenges, this work presents a blockchain-enabled medical record management system designed to provide secure and tamper-resistant data storage. The proposed system is implemented as a decentralized web application, utilizing React.js for the user interface and Web3.js or Ethers.js to enable interaction with the blockchain network. Smart contracts written in Solidity are deployed on the Ethereum platform to handle record management and enforce strict access permissions. User authentication is facilitated through MetaMask, ensuring a secure and decentralized method of identity verification. Healthcare information, including patient records, diagnoses, prescriptions, and treatment details, is maintained on the blockchain to guarantee transparency and immutability. The system empowers patients by allowing them to control access to their data, including granting and revoking permissions for healthcare providers. Tools such as Truffle and Ganache are used during development for efficient testing and deployment. In summary, the proposed solution improves data security, privacy, and accessibility, offering a dependable and scalable approach for managing healthcare records in modern digital environments.
In the ZKP community, it has long been discussed that the SumCheck protocol is asymptotically more efficient than the Number Theoretic Transform (NTT), requiring only $O(N)$ arithmetic versus $O(N \log N)$. At the same time, hardware accelerator designers propose that NTT is more hardware-friendly, benefiting from locality and data reuse, while SumCheck suffers from sequential, dependent rounds. Despite these competing intuitions, the hardware-system-level trade-offs between NTT- and SumCheck-based proving primitives remain insufficiently understood. Beyond individual accelerator design, this work presents, to our knowledge, the first hardware-system-level direct comparison of NTT- and SumCheck-based proving primitives under a unified architectural framework. We study them in the context of the ZeroCheck protocol, a common building block in zkSNARKs. We implement optimized systems for both primitives. Both are evaluated under the same level on-chip SRAM and off-chip bandwidth budgets. Our results show that there is no universal winner. Generally, SumCheck outperforms NTT for high-degree polynomials. For low-degree polynomials, performance depends on memory availability: under given SRAM budgets, NTT might deliver better performance for medium-sized workloads by exploiting data reuse. These findings, bridging cryptographic protocol design and hardware architecture, offer practical guidance for understanding the proving cost of NTT- and SumCheck-based zero-knowledge proof systems.
We extend the Lindblad Cryptography Protocol (LCP) — previously applied to consensus and decentralized finance — to the problem of verifying real-world data on-chain. Existing oracle protocols solve the immutability of records on-chain but inherit a structural weakness at the data ingestion layer: the data still originates in software, run by a trusted operator, and can be fabricated at the source before being recorded. We show that hardware with silicon-derived unforgeable identity (SRAM PUF + BCH fuzzy extractor) can sign measurements directly, producing attestations that are cryptographically verifiable by any third party without trust in the operator. We demonstrate end-to-end validation on mainnet using a live commodity price (West Texas Intermediate crude oil) sourced from the U.S. Energy Information Administration, signed by a physical node, and verified by a publicly accessible mathematical check. We further describe the generalization of this primitive across five application verticals: agriculture, energy, mining and resource extraction, Real-World Asset (RWA) tokenization, and verified ad delivery. The Lindblad Oracle complements existing oracle protocols (Chainlink, API3, UMA) by providing a hardware-anchored root of trust at the data-origination layer, beneath their data-distribution layer.
Auctions are now central to blockchain markets, settling NFT sales, token launches, DeFi liquidations, and arbitrage opportunities. Each on-chain bid is a public transaction whose inclusion is decided by a single consensus proposer per block. The proposer can observe pending bids, exclude competitors, and submit bids of their own, breaking the fairness guarantees of classical sealed-bid auctions. To enable latency-sensitive sealed-bid auctions in blockchain settings, we formalize four properties -- each necessary to prevent a concrete attack -- and design a protocol achieving all four: hiding bid contents, existence, and bidder identity until reveal (Hiding); counting all timely honest bids and rejecting late adversarial bids (Simultaneous Release); preventing silent withdrawal of committed bids (No Free Bid Withdrawal); and charging on-chain fees only to winners (Auction Participation Efficiency). Our protocol uses a timestamping oracle (instantiated with a committee of 2f_ts+1 timestampers) and a censorship-resistant inclusion predicate (instantiated using a FOCIL-based inclusion list), with only the winning bid settled on-chain. Our construction relies on two zero-knowledge proofs: an eligibility proof that anonymously proves deposit membership to the timestamping committee, and an auction proof that binds a bid to a specific auction for the inclusion list committee. We implement both using Groth16 over BN254 with Poseidon hashing in arkworks/Rust: the auction proof generates in 13 ms and verifies in under 1 ms; eligibility proofs for Merkle trees up to 2^32 bidders generate in 47-159 ms and verify in about 1 ms. Together, this yields a sealed-bid auction primitive practical for high-value, time-sensitive blockchain settings.
Despite the growing adoption of blockchains, their isolated architectures hinder seamless cross-chain communication, challenging applications that rely on integrated blockchain infrastructures, notably Blockchain-based Information Systems (BISs). Achieving interoperability while preserving privacy and regulatory compliance remains a core challenge, particularly when separate organizations operate different blockchain platforms and tokenized value must move across them without exposing transaction links that may reveal business relationships or payment behavior. Existing interoperability solutions often incur high computational overhead and rely on protocol-specific assumptions, limiting their applicability across heterogeneous blockchains. We introduce zkPACT, a privacy-preserving framework for compliant cross-chain token transfers across heterogeneous blockchains. Our framework combines Zero-Knowledge Proofs (ZKPs), oracle networks, and off-chain batching to support scalable transfers. It employs a coordinated oracle model in which validators process cross-chain burn events, while a rotating aggregator updates the shared off-chain Merkle tree after reaching consensus, enabling private and efficient token claims. To improve scalability and reduce gas costs, zkPACT batches claim requests off-chain and then submits a single succinct proof to the smart contract. To ensure validator accountability, the framework enforces an incentive mechanism and dynamic slashing. We also integrate a Know Your Customer (KYC) mechanism that enables users to demonstrate compliance without revealing sensitive data, preserving privacy and accountability in the event of abuse. We present a proof-of-concept implementation of zkPACT that achieves up to 95% lower gas costs and up to 94% lower off-chain memory usage than a non-batching approach, demonstrating its suitability for private, scalable cross-chain token transfers.
Abstract Hybrid architectures in permissioned blockchains combining on-chain policies with Threshold Proxy Re-Encryption (TPRE) suffer from a structural audit gap: cryptographic enforcement is decoupled from the ledger's state. This allows Byzantine proxies to execute unaccountable data transformations (ghost requests). Furthermore, traditional TPRE access revocation incurs O(N) linear overhead, creating a scalability bottleneck.To address these flaws, we propose DT-Share, a state-bound access control middleware. By leveraging a novel State-Bound Evidence mechanism, DT-Share cryptographically anchors TPRE outputs to the global ledger epoch. This transforms access revocation from an O(N) key-management task into a constant-time O(1) ledger state transition.A full-stack implementation using Hyperledger Fabric and IPFS demonstrates that DT-Share guarantees strict accountability with negligible overhead. Under high-concurrency workloads, it exhibits an elasticity inversion phenomenon, adaptively scaling throughput during bursty requests to provide a highly scalable, Byzantine-resistant middleware for distributed consortia.
Bilateral attribute-based access control for data trading must hide policies, provide cryptographic fairness, and avoid trusted third parties. Existing solutions either leak policy information, incur super-linear costs, or rely on trusted dispute resolution. We present PriME-Deal, a non-interactive protocol that simultaneously achieves policy-hiding bilateral matching, efficient threshold access control, and auditable fair exchange on public blockchains. The seller embeds a secret token under the buyer policy into an oblivious key-value store with pseudorandom masking; the buyer reconstructs the token locally via tag-based probing, eliminating combinatorial enumeration, and proves correctness in zero-knowledge. Fair exchange is enforced through a collateralized on-chain reveal with a cryptographic audit that penalizes misbehaviour without trusted parties. We prove security in the Universal Composability framework under standard assumptions. Compared with the state-of-the-art threshold fuzzy IB-ME scheme, the seller's publishing time is reduced by two orders of magnitude (e.g., 8.76s vs. 690s for a policy of 500 attributes). For a typical configuration of (200,20,5), the buyer completes token reconstruction and proof generation in 8.9s, with the zero-knowledge proof taking under 0.6s and remaining constant across all parameter scales. The on-chain cost is approximately 28.6M gas, well within Ethereum's block limit. PriME-Deal thus delivers the first practical privacy-preserving data trading protocol that combines linear seller overhead, bilateral policy hiding, and auditable fairness.
Data privacy concerns have become more critical than ever as machine learning and applied intelligence systems permeate sensitive industries such as healthcare, finance, national security, and personal services. This necessitates the development of privacy-preserving strategies for protecting private information while retaining the utility of intelligent models. This survey provides a comprehensive overview of privacy-preserving machine learning, with an emphasis on the cryptographic and statistical methods that are transforming how safe learning systems are built. The study starts by examining the most important components of the machine learning model and figuring out which of these may be protected to solve important privacy problems. The article then explores modern cryptographic techniques, including homomorphic encryption, zero-knowledge proofs, secure multiparty computations, and a statistical approach called differential privacy, that support contemporary privacy-preserving machine learning solutions. The study then explores how these strategies are applied independently and in hybrid systems to achieve accuracy, efficiency, and balance of privacy. This survey provides promising direction for protecting sensitive information during real-world model training and inference, offering insights into the design of trustworthy applied intelligence systems.
沈清欢, L Chen, Jimin Chen, Tao Li · 6 authors
Blockchain oracles bridge on-chain smart contracts and off-chain data sources, but encrypted off-chain data still raises two practical challenges: how to verify retrieval integrity without exposing sensitive values, and how to keep verification information fresh when the off-chain data set changes. Existing oracle and outsourced-database retrieval mechanisms often rely on plaintext verification, heavy cryptographic proofs, or static authentication structures, which limits their applicability to latency-sensitive IoT and decentralized finance scenarios. To address these issues, this paper proposes a retrieval integrity verification mechanism based on CKKS approximate homomorphic encryption and an authenticated index named CKKS-Auth Tree. The proposed mechanism verifies encrypted query results through homomorphically aggregated metadata, while smart contracts record versioned verification commitments to detect stale or replayed results after updates. The scope of the mechanism is the integrity, completeness, privacy, and freshness of data after commitment and upload; verifying the physical authenticity of the original data source is outside the core threat model. Experimental results show that the proposed scheme reduces authentication and verification overhead compared with existing retrieval verification methods while supporting encrypted metadata updates and on-chain synchronization.
The impending arrival of cryptographically relevant quantum computing threatens classical public‑key infrastructures. This paper reviews the latest developments (2025–2026) in post‑quantum cryptography (PQC), fully homomorphic encryption (FHE), and zero‑knowledge proofs (ZKP). NIST has advanced nine signature candidates to its third evaluation round and selected HQC as a backup encryption standard. Novel primitives include bio‑inspired RNA‑based cryptography, algebraic hash signatures, and topology‑mined lattice schemes. FHE has reached its fifth generation with the GL scheme and the MadPanthera virtual processor, while lightweight ZKPs such as Microsoft’s Vega enable mobile‑friendly verification. These advances demonstrate rapid maturation toward deployable quantum‑safe systems.
This paper presents TrustBridge, the first universal decentralized trust protocol integrating multi-agent LLM consensus, zero-knowledge proof generation, blockchain attestation, and natural language accessibility for real-world credential verification across employment, education, healthcare, and supply chain domains. The multi-agent consensus engine runs three independent Claude Sonnet instances in parallel, achieving 92% adversarial detection on a controlled test set — a 30 percentage point improvement over single-agent architectures. Zero-knowledge commitment schemes allow claimants to prove credential properties without revealing private values. An ERC-721 NFT certificate provides immutable on-chain attestation. This is Paper 1 of a planned two-paper series. Paper 2 will report large-scale deployment results and full ZK-SNARK integration. Targeting: IEEE Blockchain 2027