A Zero-Knowledge Proof-Driven Architecture for Privacy-Preserving Data Trading on Blockchain

The development of a robust, transparent and interoperable E-healthcare infrastructure has been a difficult task due to many regulations and legislatures like HIPAA (Health Insurance Portability and Accountability Act) and GDPR (General Data Protection Regulation). Healthcare service providers prefer to store data about their patients in locked up silos, behind often inadequate layers of security and firewalls. Such an approach results in data breaches and limits the ability to get a holistic view of the medical history of a patient. The obscure cost of treatment is another issue brought to attention recently in media. In this paper, we have proposed a national blockchain framework for managing patients' Electronic Health Records (EHRs) access control and funds in the context of India's National healthcare scheme. We introduce a transparent insurance claim process for healthcare providers and an auditable trail of EHR access using smart contracts. We use a smart card approach allowing beneficiaries to authenticate their identity using zero-knowledge proofs and delegate access to service the providers via proxy re-encryption.

The emergence of blockchain technology has revolutionized decentralized data management by offering robust alternatives to traditional centralized database systems. This paper provides a systematic and comprehensive review of blockchain-based distributed databases, highlighting key architectural transformations, core enabling technologies such as Merkle Trees, PBFT, and Zero-Knowledge Proofs, and comparing them with conventional distributed databases. Real-world implementations including Hyperledger Fabric, BigchainDB, and OrbitDB are analyzed to assess their scalability, interoperability, and security capabilities. The paper also explores intrinsic security mechanisms, performance bottlenecks, and regulatory challenges that affect adoption. Finally, it identifies open research questions and future directions necessary for building scalable, privacy-aware, and interoperable decentralized database ecosystems suitable for enterprise and multi-stakeholder environments. Keywords— Blockchain databases, consensus mechanisms, data integrity, decentralized systems, distributed ledger, Merkle trees, Zero-Knowledge Proofs

Blockchain-based solution for COVID-19 vaccine waste reduction

Data security is a major issue for smart home networks. Yet, different existing tools and techniques have not been proven highly effective for home networks’ data security. Blockchain is a promising technology because of the distributed computing infrastructure network that makes it difficult for hackers to intrude into the systems through the use of cryptographic signatures and smart contracts. In this paper, an architecture for smart home networks that could guarantee data integrity, robust security, and the ability to protect the validity of the blockchain transactions has been investigated. The system model is tested using various sizes of realistic datasets (30, 3 k, and 30 k to represent a small, medium, and large number of transactions, respectively). Four different consensus algorithms were considered, the conventional schemes concatenated hash transactions (CHT) and Merkle hash tree (MHT), as well as the newly proposed odd and even modified MHT (O&E MHT) and modified MHT (MMHT). Moreover, 15 hash functions were also examined and compared to understand the effects of each consensus algorithms on the data integrity verification check execution time and the time optimization provided by the proposed MMHT algorithm. The results show that even though the CHT algorithm gives the lowest execution time, it is impractical for a blockchain implementation due to the requirement to copy the entire blockchain ledger in real time. Meanwhile, the O&E MHT does not give any tangible benefit in the execution time. However, the proposed MMHT offers a minimum of 30% gain in time optimization than the conventional MHT algorithm typically used in blockchains. This work shows that the proposed MMHT consensus algorithm not only can identify malicious codes but has an improved data integrity check performance in smart homes, all while ensuring network stability.

– The rapid proliferation of blockchain-based decentralized applications has introduced critical security challenges ranging from vulnerable smart contracts to privacy leakage in on-chain transactions. Existing tools address these challenges in isolation, leaving practitioners to integrate disparate solutions. OmniShield is a unified, open-source blockchain security platform that consolidates AI-powered smart contract vulnerability scanning, zero-knowledge proof (ZKP) private transfers, and a private QBFT consensus network into a single cohesive system. The scanner combines static pattern analysis, symbolic execution, and a Gemini-LLM reasoning layer to detect reentrancy, integer overflow, access-control flaws, and twelve other vulnerability classes with severity ratings. Private transfers leverage Groth16 zk-SNARKs over Circom circuits so balances remain hidden on-chain while cryptographic validity is enforced. The underlying network runs on Hyperledger Besu with QBFT consensus, providing Byzantine-fault-toleran block production. Experimental results show the scanner correctly identifies known vulnerabilities in benchmark contracts, ZKP proof generation completes in under 15 seconds on consumer hardware, and end-to-end private transfers finalize within two consensus rounds. OmniShield demonstrates that enterprise-grade blockchain security can be packaged as an accessible, developer-friendly platform. Key Words: blockchain security, smart contract analysis, zero-knowledge proofs, zk-SNARKs, Hyperledger Besu, QBFT consensus, AI vulnerability scanner, reentrancy, Solidity.

Genomic data sharing remains a core problem in precision medicine because genomic data are highly sensitive and unchangeable. In this article, we propose a blockchain-based framework that utilizes zero-knowledge proofs (ZKPs), smart contracts, and off-chain storage to facilitate secure, privacy-preserving data sharing within health record systems. We implemented and evaluated a proof-of-concept prototype in Python on a simulated genomic dataset. The prototype uses a hybrid storage system where metadata is retained on a blockchain and encrypted data are placed in an emulated InterPlanetary File System (IPFS). Rule-based access is controlled using smart contracts, while privacy and security are achieved using ZKPs with interactive Schnorr protocol and elliptic curve cryptography (ECC). Empirical analysis using real-time testing over 100 iterations reported an average zero-knowledge proof with blockchain (ZKPB) query latency of 5.83 ms with a 90.00% accuracy, smart contract latency of under 0.01 ms with 90.00% accuracy, blockchain query time of 0.01 ms with 90.00% accuracy, and ECC latency of 8.72 ms with 90.00% accuracy. These empirical findings validate the effectiveness and privacy guarantees of the framework, which can be utilized in healthcare research, clinical genomics, and personalized medicine workflows.

Smart contracts self-executing code deployed on blockchain platforms have revolutionized the way digital agreements are formed and executed. Despite their decentralized nature and deterministic logic, vulnerabilities in code and execution environments can compromise their security. Cryptography is pivotal in safeguarding the integrity, authenticity, and confidentiality of smart contract operations. This paper explores cryptographic techniques that enhance smart contract trustworthiness, including digital signatures, zero-knowledge proofs, and verifiable computation. We assess how these methods reinforce security, compare frameworks across criteria like scalability and auditability, and present best practices for secure smart contract development

In a vaccine model, ensuring integrity and transparency throughout the vaccination process is crucial for reducing security risks. Therefore, developing a secure digital tracking system and regular audits becomes significant to build trust and reliability. Also, in the vaccine model, the changes are possible due to human error. The prevailing studies didn’t focus on handling the Smart Contract (SC) immutability in the vaccine model, affecting the effectiveness of the system. Thus, this paper presents a Hyperledger Fabric Blockchain (HFB) and proxy pattern SC-enabled secure vaccine model utilizing Adaptive Segmented Cache-based Merkle Tree (ASC-MT) and Manifold Deep SwAT Convolutional Neural Network (MDSCNN). Primarily, the vaccine supply chain users register in the HFB. Then, login and Quantum Cumulative Regret Cryptography (QCRC)-based vaccine and user details security are done. Afterward, the proxy pattern-based SC is created and stored in the Interplanetary File System (IPFS). Here, an ASC-MT-based tree is constructed, and hash-converted proxy pattern-based SCs are stored in ASC-MT. Subsequently, in the transaction pool, the user requests are stored. Afterward, vaccinations prioritization by BG-Fuzzy, Scaled Uniform-based Practical Byzantine Fault Tolerance (SUPBFT)-based consensus verification, and SC counterfeit detection using MDSCNN are performed. If SC is not attacked, then Merkle root verification is done. Here, if the Merkle root created by IPFS and the Merkle root created after the current transaction are matched, then only the full execution of the SC is invoked; otherwise, the system is redirected to generate the SC again. As per the outcomes, the proposed ASC-MT achieved a low tree verification time of 796 ms, and the proposed MDSCNN achieved a high accuracy of 99.78% for detecting SC counterfeits, thus outperforming prevailing techniques.

Privacy concerns of smart contracts are a major roadblock preventing their wider adoption. A promising approach to protect private data is hiding it with cryptographic primitives and then enforcing correctness of state updates by Non-Interactive Zero-Knowledge (NIZK) proofs. Unfortunately, NIZK statements are less expressive than smart contracts, forcing developers to keep some functionality in the contract. This results in scattered logic, split across contract code and NIZK statements, with unclear privacy guarantees. To address these problems, we present the zkay language, which introduces privacy types defining owners of private values. zkay contracts are statically type checked to (i) ensure they are realizable using NIZK proofs and (ii) prevent unintended information leaks. Moreover, the logic of zkay contracts is easy to follow by just ignoring privacy types. To enforce zkay contracts, we automatically transform them into contracts equivalent in terms of privacy and functionality, yet executable on public blockchains. We evaluated our approach on a proof-of-concept implementation generating Solidity contracts and implemented 10 interesting example contracts in zkay. Our results indicate that zkay is practical: On-chain cost for executing the transformed contracts is around 1M gas per transaction (~0.50US$) and off-chain cost is moderate.

Zero Knowledge Proofs (ZKPs) have emerged as transformative cryptographic primitives, enabling a wide variety of modern privacy-preserving applications across various domains. This paper presents substantial advancements in contemporary ZKPs, exploring the latest trends in ZKP schemes, novel applications, and scalable ZKP-based systems. We provide an in-depth analysis of state-of-the-art ZKP structures, including zk-SNARKs, zk-STARKs, and the more recent zk-Rollup technologies. We examine the unique properties and use cases of these techniques, highlighting their potential to enhance privacy, security, and trust in digital systems. Our research into zk-Rollups demonstrates significant improvements in transaction throughput and gas efficiency, paving the way for the extensive deployment of modern privacy-preserving solutions. Furthermore, we showcase several innovative applications of ZKPs, such as privacy-preserving decentralized finance (DeFi) protocols, anonymous credentials, and secure multi-party computation. These use cases illustrate the transformative potential of advanced ZKPs to improve privacy and security across a range of digital domains. To foster wider adoption of modern ZKPs, we have developed and opensourced a collection of advanced tools and libraries that simplify the implementation of ZKP-based solutions. We also offer practical guidance and best practices for developers and researchers working in this field, aiming to accelerate the development and real-world impact of modern zero-knowledge proof systems.

Blockchain technology has emerged in e-business as a revolutionary force in the realm of cybersecurity, offering novel solutions to the escalating challenges posed by the ever-evolving modern technology landscape. This study delves new e-business into the critical determinants that drive the application of blockchain technology in enhancing cybersecurity. With the proliferation of digital assets and sensitive information, safeguarding data integrity, confidentiality, and accessibility has become paramount. The research employs a multidisciplinary approach in e-business, drawing from the fields of cybersecurity, blockchain technology, and data management. It examines the intricate interplay between blockchain's fundamental features and their direct impact on fortifying cybersecurity measures. Key determinants explored include: Decentralization: Blockchain's decentralized architecture reduces the vulnerability of a single point of failure, rendering it more resilient against cyberattacks. Immutable Ledger: The immutable ledger ensures the integrity of stored data, making it exceptionally challenging for malicious actors to tamper with information. Smart Contracts in E-Business: The automation capabilities of smart contracts enhance the enforcement of security protocols, bolstering the protection of digital assets. Cryptography: Robust cryptographic techniques underpin blockchain security, safeguarding data from unauthorized access. Transparency: The transparent nature of blockchain allows for real-time monitoring and auditing, facilitating the early detection of security breaches. Data Privacy: Blockchain's data privacy features, including permissioned networks and zero-knowledge proofs, address concerns surrounding privacy in cybersecurity. The study also investigates real-world applications and e-business of blockchain technology in cybersecurity across industries, from financial services to healthcare and supply chain management. It highlights successful case studies and identifies the challenges and limitations faced in implementing blockchain solutions. In conclusion, this research underscores the transformative potential of blockchain technology in e-business by fortifying cybersecurity measures. By examining the critical determinants that drive its application, organizations and policymakers can make informed decisions regarding the adoption of blockchain to enhance cybersecurity in the modern technology era. The study encourages further exploration and innovation in this dynamic and rapidly evolving field to secure our digital future.

In 1998, Blaze, Bleumer and Strauss proposed new kind of cryptographic primitives called proxy re-encryption and proxy re-signature. In proxy re-encryption, a proxy can transform a ciphertext computed under Alice's public key into one that can be opened under Bob's decryption key. In proxy re-signature, a proxy can transform a signature computed underAlice's secret key into one that can be verified by Bob's public key.Proxy re-cryptography can find many interesting applications in our life. In this paper, we introduce a new attack- DDos attack against proxy in the proxy re-cryptography. Although this attack can also be implemented against other cryptographic primitives,the danger caused by it in proxy re-cryptography seems more serious.We revisit the current literature, paying attention on their resisting DDos attack ability. We suggest a solution to decline the impact of DDos attacking. Also we give two new efficient proxy re-encryption schemes which can achieve CCA2 secure based on Cramer-Shoup encryption scheme and prove its security. At last we give our conclusions with hoping researchers to pay more attention to this attack.

Cloud infrastructure refers to the dynamic provisioning of computing resources over the internet, enabling scalable and flexible enterprise operations. However, such environments face significant security challenges, particularly in access management. Cloud infrastructure delivers scalable computing resources, yet traditional Identity and Access Management (IAM) mechanisms face challenges such as centralized control, misconfigurations, and limited auditability. This study addresses these challenges by proposing a Hyperledger Fabric-based decentralized access control framework integrated with Amazon Web Services (AWS) for healthcare data security. The framework employs Zero Knowledge Proof (ZKP) for identity validation, Ciphertext Policy Attribute Based Encryption (CP- ABE) with Proxy Re-Encryption (PRE) for fine-grained data access, and machine learning driven anomaly detection for continuous monitoring. Experimental evaluation achieved throughput of 15000 transactions per second, latency of 350 milliseconds, privacy preservation up to 99.1 percent, and anomaly detection accuracy of 99.63 percent, surpassing prior models significantly. Storage analysis demonstrated predictable scalability with encrypted medical records up to 20 MB, while token revocation time remained within 1.9 seconds under network stress. The results confirm that blockchain-based access control enhances security, privacy, and auditability while maintaining operational efficiency. This research establishes a scalable and tamper-resistant model for secure healthcare data management in cloud environments.

For over 20 years, black-box impossibility results have been used to argue the infeasibility of constructing certain cryptographic primitives (e.g., key agreement) from others (e.g., one-way functions). A widely recognized limitation of such impossibility results, however, is that they say nothing about the usefulness of (known) nonblack-box techniques. This is unsatisfying, as we would at least like to rule out constructions using the set of techniques we have at our disposal. With this motivation in mind, we suggest a new framework for black-box constructions that encompasses constructions with a nonblack-box flavor: specifically, those that rely on zero-knowledge proofs relative to some oracle. We show that our framework is powerful enough to capture the Naor-Yung/Sahai paradigm for building a (shielding) CCA-secure public-key encryption scheme from a CPA-secure one, something ruled out by prior black-box separation results. On the other hand, we show that several black-box impossibility results still hold even in a setting that allows for zero-knowledge proofs.

This article investigates decentralized blockchain technology to improve the management of sustainability in prefabricated buildings. By utilizing a public blockchain and a private blockchain together, both real-time recording and management of construction-related data, and contract management-applied automation are accomplished. Smart contracts, Merkle trees, and Proof of Work (PoW) consensus mechanisms guarantee the security, reliability, and transparency of data, especially with respect to those categories including material qualifications, construction progress, and quality inspections. The Hyperledger Fabric platform incorporates encryption technology combined with smart contracts for additionally protecting the privacy of financial data, construction progress, and supply chain data through use of the AES-256 algorithm encryption and strict data audit monitoring controls. Moreover, decentralized blockchain technology improves transparency and controllability of data systems, effectively decreasing the risk of data compromise, and optimizing the management of the supply chain through smart contracts, hash value technology, and other means. Tracking time through the average supply chains is 6.1 s, the average accuracy for fulfillment of contracts is 98.36%, the average success rate for smart contract execution is 98.84%, and the average timeliness of information flow is 95.12%. This article promotes the digital transformation and sustainable development of the construction industry by improving the prefabricated construction sector's capacity for sustainable development and offering fresh concepts for data management and monitoring.