P. Subramanya Sai, Bhukya Niranjan, Akula Tejaswini, A Varshitha · 5 authors
The exponential increase in digital data exchange and online communication has intensified the need for secure, transparent, and dependable file-sharing systems. Critical information such as financial records, healthcare data, confidential documents, and research outputs is frequently transmitted across distributed networks, where conventional centralized storage models introduce significant vulnerabilities. These traditional systems rely on single-point control, making them prone to data breaches, unauthorized access, service disruptions, and integrity violations. Furthermore, they lack transparency and robust audit mechanisms, raising concerns about data reliability and trustworthiness during storage and transmission. To overcome these limitations, this work proposes a decentralized and secure file-sharing framework that integrates blockchain technology, the Inter-Planetary File System (IPFS), and cryptographic techniques. The system ensures data confidentiality by encrypting files using the Elliptic Curve Integrated Encryption Scheme (ECIES) before storing them in the distributed IPFS network. Instead of placing the actual data on-chain, only essential metadata including file hash, ownership details, timestamps, and access permissions is maintained within a smart contract on the Ethereum blockchain. This design guarantees immutability, traceability, and protection against tampering, while enabling fine-grained access control. In addition to secure storage, the framework incorporates ChaCha20-based symmetric encryption to evaluate and compare computational performance with asymmetric methods. The combination of decentralized storage, cryptographic security, and immutable ledger technology eliminates reliance on centralized authorities, thereby reducing single points of failure and enhancing system resilience. The proposed approach ensures that only authorized entities can access and decrypt shared content while maintaining transparency of file transactions.
The rapid advancement of digital technologies in healthcare has increased the need for secure, transparent, and efficient management of medical data. However, most existing systems rely on centralized architectures, where sensitive patient information is controlled by a single authority. This creates vulnerabilities such as data breaches, unauthorized access, and single points of failure, which can compromise data integrity and patient privacy. The core problem addressed in this research is the lack of a decentralized and tamper-resistant mechanism for managing Electronic Health Records (EHR). Current solutions often suffer from limited transparency, inefficient data sharing between patients and doctors, risks of data manipulation, dependency on intermediaries, and scalability issues due to large medical files like reports and prescriptions. To address these challenges, this research proposes a blockchain-based healthcare management system integrated with the Inter-Planetary File System (IPFS). Blockchain technology, implemented using Ethereum and Web3, ensures secure, immutable, and transparent transaction handling through smart contracts. IPFS is used for decentralized storage of medical files, with only cryptographic hashes stored on the blockchain to reduce storage overhead while maintaining data integrity. The system enables patients to book appointments, upload medical reports, and securely share them with doctors. Doctors can access records, provide diagnoses, and generate prescriptions, which are also stored via IPFS and linked to the blockchain. This ensures that data cannot be altered without detection, enhancing trust. The proposed system improves data security, privacy, reliability, and scalability in healthcare data management.
In decentralized finance (DeFi), accidental cryptocurrency transfers to incorrect wallet addresses are a large usability and security issue, frequently causing permanent loss of funds. We present CryptoSafeSend, a smart contract-based safety protocol for transactions featuring a cryptographically secure passcode verification scheme supporting conditional transfers. This work addresses higher-level security issues by introducing a PBKDF2-based key derivation function, which generates strong encryption keys based on Firebase's Firebase Unique Identifier. Secret passcodes are encrypted in Advanced Encryption Standard operating in Galois/Counter Mode functions deployed underneath the Web Crypto API, and the initialization vector and ciphertext are Base64 encoded for off-chain reliable storage and Firebase Firestore-based messaging. The protocol prevents unauthorized exploitation by safely binding off-chain passcode transmission to a matching on-chain verification, reinforcing user trust without undermining decentralization. Also, to ensure recoverability, CryptoSafeSend integrates a 7-day on-chain escrow lock, after which unclaimed funds become permissionlessly refundable to the sender, preserving decentralization while eliminating reliance on trusted intermediaries. Testing on an Ethereum testnet confirms negligible gas overhead, immunity against double claims, and strong security guarantees, qualifying CryptoSafeSend as a valuable constituent in next-generation secure digital asset protocols.
Muhammad Ahmad, Hua Zhou, Tanzeela bibi, Haider Ali
In today's digital environment, the swift advancement of interconnected technologies has raised significant worries about data safety, privacy, and reliability. The Internet of Things (IoT), networking systems, and cloud services produce and transfer large quantities of sensitive information, leaving them susceptible to cyber threats and other security risks. This research offers a detailed evaluation of how cryptography, network protection, and digital forensics work together, highlighting their combined impact on securing communication, safeguarding data integrity, and ensuring effective investigation methods. The approach to research relies on a thorough examination and combination of available literature, with a focus on major developments in cryptographic methods, network defense strategies, and forensic analysis frameworks. Particular focus is given to Homomorphic Encryption (HE), which allows processing to occur directly on encrypted information without the need for decryption, thus increasing privacy in unreliable settings such as cloud services and IoT environments. Moreover, the research includes new strategies in blockchain-centered forensics, featuring automated cost management that aligns with regulations, mapping wallet interactions, and utilizing non-fungible tokens (NFTs) as reliable audit references to enhance transparency and responsibility. The results show that cryptographic methods ensure safe data transfer, while network security strategies defend systems against unauthorized access, misuse, and cyber intrusions. At the same time, digital forensics offers a scientifically supported method for finding, preserving, and examining digital proof, tackling key evidentiary issues in today's cyber landscape. The integration of blockchain forensics and NFTs further boosts auditability, traceability, and trust, especially within decentralized finance (DeFi) setups and intricate digital transactions. In summary, the alignment of cryptography, network protection, and digital forensics creates a strong and forward-thinking security framework that improves data safety, helps with regulatory adherence, and enhances the overall durability of contemporary digital systems.
In the context of banking systems increasingly relying on cloud computing platforms, protecting sensitive data while maintaining processing performance is a major challenge. This paper presents and evaluates a cloud banking data processing model that integrates Homomorphic Encryption (HE), Zero-Knowledge Proof (ZKP), and the ORAM protocol to achieve a balance between security and performance. Experiments were conducted on a real Bank Marketing (UCI) dataset with 5000 records, using DSL query operations to calculate the average balance, count high-balance customers, total call duration, and savings deposit acceptance rate. The results show that the combination of HE, ZKP, and ORAM significantly improves security but increases computational cost; however, a suitable configuration can significantly reduce latency while still meeting security requirements. A detailed analysis of the security-performance trade-off provides an important empirical basis for implementing banking data security solutions in the cloud.
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.
Cloud storage systems have become an integral part of modern data management by enabling users to store and access data remotely.However, traditional cloud storage architectures rely on centralized servers, which introduce several critical challenges such as single-point failure, redundant data storage, increased storage costs, and security vulnerabilities.In earlier systems, data was stored in centralized data centers where duplicate files were repeatedly maintained, leading to inefficient utilization of storage resources.Although basic deduplication methods were implemented, they often compromised data confidentiality and lacked transparency in metadata management.Furthermore, failure of the central server could result in permanent data loss.To overcome these issues, this research proposes the Blockchain-enabled Heuristic Optimized Deduplication Model (BHODM), which integrates blockchain technology, InterPlanetary File System (IPFS), Convergent Encryption (CE), and heuristic-based chunking techniques.In this model, files are divided into optimized chunks based on file size using a heuristic approach.Each chunk is encrypted using CE, where the encryption key is derived from the hash of the data itself, allowing secure deduplication without exposing plaintext data.Duplicate chunks are identified through hash comparison, ensuring that only unique data is stored.The encrypted chunks are stored in IPFS, a decentralized peer-to-peer storage network, while metadata such as file names, block numbers, and hash values are securely maintained in an Ethereum blockchain smart contract, ensuring immutability and transparency.The system is implemented using Django, Web3, IPFS API, and AES-CTR encryption.Experimental results based on storage utilization and computation time demonstrate improved efficiency over traditional approaches.
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.
The exponential growth of digital data has intensified reliance on cloud storage, yet conventional centralized architectures remain persistently vulnerable to unauthorized access, data tampering, and privacy violations. This paper presents a novel blockchain-driven approach for decentralized cloud storage that addresses these concerns through a multi-layered security mechanism. The proposed system fragments a user’s file into multiple independent blocks, encrypts each block using the AES-256 algorithm with PBKDF2-derived keys, and distributes them across distinct nodes of the InterPlanetary File System (IPFS). The corresponding IPFS hash addresses are then recorded on an Ethereum-based blockchain through a Solidity smart contract, ensuring immutability and tamper-resistance of the entire storage index. During file retrieval, the system queries the blockchain to collect all block hash addresses, fetches encrypted blocks from IPFS, reassembles them in the correct sequence, and delivers the decrypted output to the user. The implementation is built using Python, Django, Web3.py, and the Truffle/Ganache development environment, and has been functionally verified across all core user-facing modules.
Cloud storage systems have become an essential component of modern data management, enabling users to store and access data remotely. However, traditional cloud storage architectures rely on centralized servers, which introduce critical challenges such as single-point failure, redundant data storage, high storage costs, and security vulnerabilities. In earlier systems, data was stored in centralized data centers where duplicate files were often saved multiple times, leading to inefficient utilization of storage resources. Although basic deduplication techniques were used, they frequently compromised data confidentiality and lacked transparency in metadata management. Moreover, failure of the central server could result in permanent data loss. To overcome these limitations, this research system integrates blockchain technology, InterPlanetary File System (IPFS), Convergent Encryption (CE), and heuristic-based chunking techniques to create a secure and decentralized storage framework, hereafter named Blockchain-enabled Heuristic Optimized Deduplication Model (BHODM). In this system, files are divided into optimized chunks using a heuristic method based on file size. Each chunk undergoes CE, where the encryption key is derived from the hash of the data itself, enabling secure deduplication without exposing plaintext information. Duplicate chunks are identified using hash comparison, ensuring that only unique data is stored. The encrypted chunks are stored in IPFS, a decentralized peer-to-peer storage network that eliminates reliance on a single server. Metadata such as file names, block numbers, and hash values are securely stored in an Ethereum blockchain smart contract, ensuring immutability and transparency. The system is implemented using Django for the web application, Web3 for blockchain interaction, IPFS Application Program Interface (API) for distributed storage, and Advanced Encryption Standard in Counter Mode (AES-CTR) encryption for security. By combining decentralized storage, blockchainbased metadata management, and secure deduplication, the proposed model effectively reduces storage overhead, enhances data integrity, and mitigates single-point failures. The system is further evaluated using storage utilization and computation time analysis, demonstrating improved efficiency compared to traditional approaches
The rapid adoption of digital healthcare systems has significantly increased the use of Electronic Health Records (EHR), online appointment platforms, and digital prescription management. While these technologies enhance accessibility and operational efficiency, they also introduce critical challenges related to data confidentiality, secure authentication, record integrity, and protection against unauthorized access. Healthcare data contains highly sensitive personal and medical information, making security a primary concern. Ensuring secure communication and verified access between patients and doctors remains a major challenge in maintaining trust and privacy within digital healthcare environments. Many existing healthcare management systems rely on centralized storage models and basic authentication mechanisms, exposing them to risks such as data breaches, impersonation attacks, and unauthorized record modification. Although basic encryption mechanisms may be applied to protect stored data, key management and authentication processes often rely on standard approaches without decentralized verification or advanced cryptographic reinforcement. As a result, centralized architecture creates a single point of failure, increasing vulnerability to unauthorized access, data tampering, and weak identity verification. Limited transparency and auditability further restrict effective monitoring of data usage and system activities. To address these issues, the proposed system introduces Quantum Crypt (QC), a hybrid security approach that integrates blockchain technology with Post-Quantum Cryptography (PQC) concepts and advanced encryption mechanisms. Medical reports and prescriptions are secured using the Advanced Encryption Standard in Cipher Block Chaining mode (AES-CBC), with encryption keys generated through a quantum-inspired mechanism. Authentication is enhanced through a lattice-inspired model implemented via Qiskit-based quantum circuit simulation to ensure secure key validation between patients and doctors. Blockchain integration using Web3 and smart contracts ensures immutable storage of healthcare records, improving transparency, strengthening data integrity, and enabling controlled access within the digital healthcare ecosystem.
The rapid evolution of cloud computing has revolutionized digital data storage and sharing, enabling users to access information anytime and anywhere. Despite these advantages, cloud-based systems face major challenges related to data security, privacy protection, and trust management, particularly when handling sensitive user information. Conventional cloud storage solutions operate on centralized architectures, where a single cloud service provider manages and controls the stored data. This centralized model introduces significant risks, including single points of failure, unauthorized data access, data manipulation, and limited visibility into data-sharing activities. In many traditional systems, data protection mechanisms rely on basic encryption methods without strong auditing or verification features, leaving them vulnerable to insider attacks and external cyber threats. Furthermore, the absence of immutable transaction records and robust key management practices reduces accountability and weakens user confidence in cloud environments. To address these shortcomings, the proposed system presents a secure cloud data sharing framework that combines Elliptic Curve Cryptography (ECC) with blockchain technology. In this approach, user files are encrypted using ECC before being uploaded to the cloud, ensuring strong data confidentiality and protection against unauthorized access. Simultaneously, blockchain technology is employed to record file metadata and transaction details in a decentralized and tamper-resistant ledger, enabling transparent and verifiable audit trails. The decentralized architecture eliminates reliance on a single authority, enhances trust, and prevents unauthorized modification of stored records. Additionally, secure authentication and controlled access mechanisms further reinforce system security. By integrating advanced cryptographic encryption with decentralized verification, the proposed solution enhances data integrity, improves transparency, and establishes a reliable and accountable framework for secure cloud data sharing.
Abstract Non-Fungible Tokens (NFTs) are blockchain-based digital assets that provide verifiable proof of ownership and authenticity. Despite their rapid proliferation, NFT markets face ongoing challenges related to user trust, legal ambiguity, and sustainable technological integration. We offer a comprehensive hybrid review by combining bibliometric and systematic approaches of 190 peer-reviewed NFT-related articles published since 2022. Through structured keyword mining, abstract-level thematic classification, and co-occurrence network visualization, we trace the intellectual evolution of NFT research across disciplines and time. Our analysis spans 119 journals and identifies six major thematic clusters: User and Market Dynamics Legal and Ethical Considerations Blockchain and NFT Technology Applications and Use Cases Digital Transformation and Innovation and Challenges and Issues . Temporal keyword trends reveal a progression from foundational blockchain infrastructure to user adoption and experiential design, toward regulatory integration, metaverse ecosystems, and industry-specific deployments in the recent years. Network visualizations highlight converging interests in topics such as decentralized identity, interoperability, and sustainability. In addition to mapping existing knowledge, this review identifies critical research gaps in areas such as regulatory frameworks, long-term infrastructure design, socioeconomic inclusion, and trust verification mechanisms. These findings offer a forward-looking research agenda centered on standardization, interdisciplinary integration, and user-centric innovation, paving the way for a more resilient and inclusive NFT ecosystem.
Vaishnavi S. Jadhav, Sakshi S. Niphade, S. S. Mahale
Secure data sharing has become a critical challenge in modern digital ecosystems due to increasing data breaches, lack of transparency, and dependence on centralized authorities. Traditional data-sharing mechanisms often suffer from single points of failure, unauthorized access, and limited trust among participating entities. Blockchain technology, with its decentralized, immutable, and cryptographically secure architecture, offers a promising solution to these challenges. This research paper explores the application of blockchain technology for secure data sharing, emphasizing its ability to ensure data integrity, confidentiality, transparency, and access control. The study examines how features such as distributed ledgers, smart contracts, and consensus mechanisms can be leveraged to manage data ownership, enforce access policies, and prevent tampering. Various blockchain-based data-sharing models are reviewed across domains such as healthcare, finance, and supply chain management. The paper also discusses key challenges, including scalability, privacy preservation, interoperability, and regulatory concerns. Finally, future research directions are highlighted to enhance the efficiency and practicality of blockchain-enabled secure datasharing systems
• The STipChain+ system employs a combination of cryptographic accumulators and verifiable computing techniques to create a stateless blockchain for smart contracts. This system offers a solution for the use of blockchain in big data scenarios. • A new hierarchical group commitment scheme for smart contracts based on the RSA cryptographic accumulator has been developed with the objective of reducing the storage overhead of contract evidence in the system by 99 • Design a composite RSA accumulator scheme for decentralised SGX Remote Attestation under stateless conditions. This scheme should transfer the trust in Intel to the trust in the group of nodes on the chain, and accumulate the certificate information through cryptographic accumulator technology. This should reduce the burden of storage on the system and reduce the dependence on a single organisation. • The experimental results demonstrate that, while maintaining decentralisation and security, STipChain+ can significantly reduce the storage pressure on consensus nodes, thereby enhancing system throughput. Blockchain is regarded as one of the most transformative and innovative technological developments of recent times, due to its decentralised nature. Nevertheless, the majority of public chains are currently grappling with the challenge of exponential data growth within the block chain system, largely due to the presence of high levels of data redundancy, which is resulting in a significant consumption of node storage resources. However, the scheme is subject to several limitations, including the storage overhead associated with contract evidence under the conditions of extensive smart contracts and the necessity of placing trust in the central node for the purpose of verifying smart contracts. The objective of this paper is to propose a new stateless blockchain architecture, designated as STipChain+. The STipChain+ system enables the real-time computation of contract evidence and the completion of the execution and verification of smart contracts without compromising the decentralization of the blockchain. The layered grouping design of smart contracts enables the reduction of the data involved in generating contract evidence, thus resolving the shortcomings of the existing stateless blockchain scheme, which necessitates the pre-calculation of evidence and its subsequent update in a sequential manner. Furthermore, the storage of substantial amounts of evidence is also alleviated. In addition, the issue of the trusted third party when verifying smart contracts is further addressed by proposing a composite RSA accumulator certificate commitment scheme with a new smart contract execution logic and transaction verification method. The results of experimental studies indicate that STipChain+ reduces the storage requirements for state data by 99% in comparison to existing blockchain storage optimisation schemes. This is achieved without the introduction of third-party trusted entities, and the reduction in storage requirements can be verified in a fixed amount of time for any smart contract.
Cloud computing has transformed data storage, accessibility, and enterprise operations; however, it has also increased exposure to sophisticated cyber threats. Traditional centralized Identity Management Systems (IDMs) often suffer from critical vulnerabilities such as a single point of failure, where the compromise of a central authority can expose sensitive user credentials. This research proposes ZKP-Shield, a security framework that integrates Non-Interactive Zero-Knowledge Proofs (NIZKPs) with a Software-Defined Perimeter (SDP) to create a secure and invisible cloud authentication environment. The proposed architecture eliminates the need to transmit passwords or sensitive identity data by allowing users to mathematically prove their identity without revealing secret information. Simultaneously, the SDP layer conceals cloud resources from unauthorized users by enforcing a “dark cloud” model, where services remain hidden until authentication is successfully verified. The framework employs cryptographic techniques such as the Discrete Logarithm Problem and the Fiat–Shamir heuristic to transform interactive proofs into efficient non-interactive authentication processes. Experimental simulations conducted in a distributed cloud environment demonstrate that the ZKP-SDP integration significantly reduces attack surfaces, prevents credential-based attacks, and maintains acceptable latency for enterprise applications. The results indicate that combining cryptographic identity verification with network invisibility provides a scalable and resilient security model for modern cloud infrastructures.
Tuan Nguyen Kim, Ha Nguyen Hoang, Son Doan Trung, Lam Nguyen
Cloud computing has become a vital platform for large-scale data analytics, yet it poses significant privacy challenges when handling sensitive information, especially in healthcare and financial domains.Homomorphic Encryption (HE) enables computation on encrypted data, providing strong privacy guarantees, but traditional HE frameworks lack efficient query representation, do not protect query patterns, and cannot prove correctness of cloud-side computations.This paper proposes HE-Cloud, an integrated privacy-preserving framework that combines DSL-driven query compilation, HE, Zero-Knowledge Proofs (ZKP), and Oblivious RAM (ORAM).Our framework allows clients to express high-level analytical queries, securely executes them on encrypted data, protects query access patterns via ORAM, and returns verifiable results through ZKP.A proof-of-concept implementation using the Pima Diabetes dataset demonstrates feasibility: Average glucose computations can be performed entirely on encrypted data with sub-second latency for homomorphic operations and minimal accuracy loss (approximately 0.001).Scalable secure analytics, extendable to larger datasets and machine learning tasks.
Every standard signature scheme enforces one property: only the key holdercan sign. What the key holder signs is unconstrained. Policy enforcement-- spending limits, rate limits, access control -- lives in smartcontracts, middleware, or governance: layers that can be upgraded,bypassed, or exploited. We call this the software-layer assumption:compliance holds only if the enforcing code is correct and unmodified. We eliminate this assumption. We introduce behavior-bound signatures(BBS), in which a policy constraint delta(x) < epsilon is committed atkey generation and enforced inside the signature's zero-knowledge proof.If the action violates the policy, the ZK constraint system isunsatisfiable -- no witness, no proof, no signature. This is not asoftware check. It is a mathematical impossibility. No software canoverride. Unlike policy-based signatures (where an authority imposes policy onsigners), BBS is self-committed: the signer binds their own futurebehavior at key generation, and even the signer cannot later violate orrevoke this commitment. We formalize this as policy-soundness (PS-CMA), a security modelstrictly stronger than EUF-CMA, and prove it under standard assumptions(Pedersen binding, Poseidon CR, ZK knowledge soundness). From thissingle primitive, five independent consequences follow -- not as separatedesigns, but as necessary implications of one cryptographic root: (A) Compliance safety under f <= n-1 Byzantine faults, decoupled from honest-quorum assumptions.(B) O(1) verification and audit via a single ZK check and Pedersen homomorphic aggregation.(C) Elimination of the virtual-machine execution layer for policy-constrained transactions.(D) A gasless ledger: branch C removes metering, while ZK-encoded rate limits make spam mathematically nonexistent.(E) The first cryptographic guarantee that a compromised autonomous AI agent cannot exceed its authorized behavioral envelope.
Open access
3 source records
Cryptography and Data Security
Advanced Authentication Protocols Security
Physical Unclonable Functions (PUFs) and Hardware Security
The proliferation of cloud infrastructures has intensified concerns regarding data security, integrity, identity and access management, and user privacy. Despite recent advances, existing solutions often lack comprehensive integration of privacy-preserving mechanisms, dynamic trust management, and cross-provider interoperability. This study proposes an AI-enabled, zero-trust, blockchain-fused identity management framework for secure, privacy-preserving multi-cloud environments. The framework integrates homomorphic encryption with differential privacy for aggregate-level protection and secure multi-party computation for collaborative data processing. The proposed system was validated in a simulated multi-cloud environment using CloudSim, Ethereum blockchain, and AWS EC2. Experimental results indicate homomorphic encryption latency of approximately 450ms per operation and statistically significant security improvements (t(128) = 12.47, p < 0.001), privacy (t(95) = 8.93, p < 0.001), and throughput (t(156) = 15.21, p < 0.001). The framework achieved differential privacy with ε = 0.1 while retaining 99.2% data utility, and demonstrated a 34% improvement in processing speed over conventional differential privacy approaches. In addition, the implementation was observed to be 2.3× faster than BGV-based configurations, with 45% lower memory consumption than CKKS and a 67% reduction in ciphertext size relative to baseline implementations. From an operational perspective, the framework shows a 23% reduction in security management costs, a 31% improvement in resource utilization efficiency, and an 18% decrease in compliance audit expenses. The model further indicates a 27% reduction in total cost of ownership (TCO) compared with multi-vendor security solutions, a projected return on investment (ROI) within 14 months, and an 89% reduction in security incident response costs under the evaluated conditions.
Zero-knowledge (ZK) proofs can be formally correct while their deployment pipelines remain fragile. The practical failure modes often arise not at the proof layer, but at the layers where trust is injected: setup, key custody, entropy sourcing, implementation, governance, and deployment interfaces. This paper models ZK pipelines as trust-graphs and proposes an audit-first separation between (i) proof correctness and (ii) pipeline integrity. The core claim is structural: for any non-trivial ZK pipeline, there exists at least one responsibility binding layer R where trust is required and accountability must be assigned. Removing a ceremony does not remove responsibility; it relocates it. We provide minimal definitions, a traceable audit interface, and compact structural examples intended to support reproducible security reviews without overclaiming. Keywords: zero-knowledge; trusted setup; CRS; SNARK; STARK; trust graph; audit; governance; pipeline integrity; responsibility relocation
This study develops a blockchain-enabled framework to improve educational administration data sharing by addressing persistent challenges related to data silos, security risks, trust deficits, and inefficient approval workflows that hinder cross-institutional collaboration. The approach examines the alignment between blockchain capabilities and data-sharing requirements and designs a consortium-chain implementation pathway that integrates distributed ledgers, smart contracts, encryption, and dynamic authorization across both standardized and emerging scenarios. A multi-province pilot involving 40 institutions was conducted to evaluate impacts on efficiency, security, and user trust. The results demonstrate an 89% reduction in processing time, near-zero internal tampering, substantial decreases in error rates, and significant improvements in perceived data credibility and clarity of rights and responsibilities. These findings indicate that blockchain can function as a foundational trust infrastructure, supporting the development of secure, accountable, and scalable educational data ecosystems.
The rapid growth of decentralized systems in theWeb3 ecosystem has introduced numerous challenges, particularly in ensuring data security, privacy, and scalability [3, 8]. These systems rely heavily on distributed architectures, requiring robust mechanisms to manage data and interactions among participants securely. One critical aspect of decentralized systems is key management, which is essential for encrypting files, securing database segments, and enabling private transactions. However, securely managing cryptographic keys in a distributed environment poses significant risks, especially when nodes in the network can be compromised [9]. This research proposes a decentralized database scheme specifically designed for secure and private key management. Our approach ensures that cryptographic keys are not stored explicitly at any location, preventing their discovery even if an attacker gains control of multiple nodes. Instead of traditional storage, keys are encoded and distributed using the BFLUT (Bloom Filter for Private Look-Up Tables) algorithm [7], which enables secure retrieval without direct exposure. The system leverages OrbitDB [4], IPFS [1], and IPNS [10] for decentralized data management, providing robust support for consistency, scalability, and simultaneous updates. By combining these technologies, our scheme enhances both security and privacy while maintaining high performance and reliability. Our findings demonstrate the system's capability to securely manage keys, prevent unauthorized access, and ensure privacy, making it a foundational solution for Web3 applications requiring decentralized security.
This article explores the role of zero-knowledge cryptographic proofs as a basic trust mechanism for financial and government digital services. The theoretical section explains how such proofs shift compliance verification from a "reveal data and verify" mode to a "prove property and admit access to service" mode, thereby reducing transaction costs, mitigating information asymmetries, and limiting agency costs. Drawing on insights from new institutional economics and mechanism theory, it demonstrates how formalized verifiability improves rule robustness, makes truthful reporting individually rational, and reduces the negative externalities of leaks. The analytical section systematizes classes of constructions, highlighting tradeoffs between proof size, latency, the need for trusted configuration, and operational risks. The practical section describes applications in payment infrastructure, lending, insurance, cross-border settlements, digital identity, and ledger management: range constraint verification, threshold and attribute verification, verifiable computation, and selective disclosure. It is demonstrated that with proper design, it is possible to combine data minimization with targeted transparency and effective enforcement, including in projects involving central bank digital money and pan-European identity wallets. Implementation metrics are discussed: marginal cost of proof and verification, average latency, fault tolerance, and the proportion of cases where primary documents are replaced with proof of property.
Blockchain technology, with its characteristics of decentralization, immutability, auditability, and traceability, has gradually become a core infrastructure in the digital economy era, demonstrating great potential in fields such as finance, government services, and the Internet of Things (IoT). However, as the scale of blockchain networks expands and data volumes surge, issues such as full-node storage redundancy, limited transaction throughput, and inefficient synchronization of historical data have become increasingly prominent, severely restricting the large-scale application of blockchain systems. The storage scalability problem faced by blockchain is therefore becoming more critical. To address the challenge in which on-chain storage expansion still cannot meet the demand for large-scale data storage, a storage method combining the InterPlanetary File System (IPFS) with blockchain, referred to as IPFS-BC, is proposed. In IPFS-BC, large-scale raw data are stored in the decentralized and content-addressable IPFS network, while the blockchain only retains the unique content identifier (CID) hash and related metadata. Through smart contracts enabling dynamic permission management and fine-grained access control, efficient interaction and collaborative storage between on-chain and off-chain systems are achieved. In this work, file upload simulation experiments were conducted, and two evaluation indicators—storage space consumption and storage performance (file read/write time and speed)—were used to compare three storage approaches: Distributed Hash Table (DHT)-based off-chain storage, Financial Blockchain Shenzhen Open Source (FISCO BCOS) on-chain storage, and the IPFS-BC on-chain/off-chain collaborative storage model. Experimental results show that the IPFS-BC model reduces storage space consumption by approximately 75% compared with FISCO BCOS blockchain storage when storing file data, significantly decreasing data redundancy. Moreover, IPFS-BC ensures system security during the on-chain process, and through the automated management and auditing provided by smart contracts, it effectively enhances system security and realizes scalable on-chain/off-chain collaborative storage.