Adil Raja, Ragini Kushwaha, Muhidinov Ayubbek Nuritdinovich, Girish H · 6 authors
The fast-growing Internet of Things has opened up new possibilities of automation, connectivity, and intelligent decision-making in smart environments. Nevertheless, the problems of security, transparency, and control decentralization in resource-limited IoT networks remain major issues. A potential solution is blockchain technology; however, conventional consensus systems, such as Proof-of-Work and Proof-of-Stake, are not suitable for IoT applications because they are energy- and computationally intensive and not scalable. This research paper suggests an architecture of a secure and efficient automation of smart homes with real-time blockchain recording facilitated by a Lightweight Delegated Byzantine Fault Tolerance (LdBFT) protocol. The design provides solutions to major issues of the IoT system such as security, decentralization and scalability by proposing a lightweight consensus mechanism which is appropriate in resource constrained systems. The proposed study enhances the effectiveness of the IoT blockchain systems in terms of efficiency, security, and scalability. LdBFT protocol streamlines consensus functions with lightweight delegation and priority-based validation, which further guarantees low latency and energy usage as well as reliability and security in communication among distributed internet of thing devices in real-time smart homes. Experimental analysis demonstrates that the LdBFT protocol significantly reduces consensus wait time, increases fault tolerance against malicious or failed nodes, and consumes less energy than traditional blockchain protocols. Overall, the proposed system offers a scalable, resource-efficient, and secure blockchain architecture for use in smart home IoT settings.
This seminar paper presents a comprehensive study on blockchain interoperability, focusing on enabling communication between independent blockchain networks. It examines key techniques such as cross-chain bridges, atomic swaps, relay chains, and oracle-based solutions. The paper also analyzes major platforms like Polkadot, Cosmos, and Chainlink, highlighting their roles in improving scalability and efficiency. Additionally, it discusses the challenges, security concerns, and limitations of interoperability while proposing a hybrid framework to enhance secure and reliable cross-chain communication. The study emphasizes the importance of interoperability in advancing decentralized applications and the future of Web3 technologies.
Abstract – 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.
Cryptocurrency market infrastructure—public blockchains and cross-chain bridges supporting tens of billions in liquidity—is monitored as a systemic-risk surface by the Financial Stability Board and equivalent bodies, with defensive posture calibrated against human-level adversaries. Anthropic’s April 2026 release of Claude Mythos Preview has prompted institutional response across financial regulation but no blockchain-specific analytical framework. This paper develops one by defining Mythos-class as a vendor-neutral capability profile: a set of frontier autonomous offensive capabilities specified independently of any single model or vendor (defined by five constituent capability primitives). The central analytical claim is friction inversion: the patch primitives, segmentation, vendor-coordinated disclosure, and credential rotation that constrain Mythos-class capability in conventional IT environments are structurally absent on-chain. This makes blockchain exposure positioned differently in kind, not degree, from enterprise IT. The paper instantiates this finding against Bitcoin and Ethereum/L2 architectures through analysis of four major bridge exploits totaling over $1.74 billion in losses. Vendor-neutral defensive and governance frameworks defined against the capability profile rather than any specific model release are the correct unit of analysis. On this basis the paper offers general recommendations for protocol governance, audit and verification cadence, and regulatory posture, developed as an analytical framework rather than as empirically validated risk estimates.
Blockchain technologies are making it possible to develop crypto-currencies and programmable smart contracts that can work in worldwide trustless and decentralized environments. Decentralized autonomous organizations (DAOs) that can coordinate the works of crowds of users, developers, and researchers can be built using smart contracts on blockchains. We contribute a decentralized autonomous software organization model and an Ethereum blockchain-based smart contract named AutonomousSoftwareOrg that provides a continuously operating virtual organization for open-source software development communities and users. AutonomousSoftwareOrg provides a project funding mechanism based on crypto-currencies, a decision-making mechanism based on voting, and recordkeeping for software usage citations and executions. Furthermore, software executions, along with their input and output data files, can also be transactionally recorded in AutonomousSoftwareOrg. This enables software execution graphs to be constructed for analysis. An AND/OR graph model of input/output data and software executions is presented, along with analysis algorithms for execution traceability and reproducibility assessment. AutonomousSoftwareOrg is deployed and tested on the Ethereum-based Bloxberg blockchain network which is operated by academic and research institutions, demonstrating its practical viability for sustainable open-source software development.
The growth of cryptocurrencies and blockchain technology has spawned a massive revolution in the traditional banking and financial system. The trend in modern digital transactions is towards platforms that are transparent, secure, and decentralized. Now blockchains and cryptocurrencies are actively used in order to provide reliable financial communication and data exchange, but their effectiveness and safety depend on the properly developed mathematical principles. Mathematics forms the foundation of functionality, reliability, and security that blockchain and cryptography systems rely on. An example of such cryptographic hash functions is that they can ensure the integrity and immutability of data in blockchain records, which makes any change of the information stored in blockchain records extremely hard without being detected and therefore protects the system against tampering and cyber threats. Digital signatures and public-key cryptography ensure safe user authentication and validation of transactions in the decentralized networks. Another critical aspect of blockchain technology that is based on the mathematical modelling is consensus mechanisms. Conventional methods like Proof of Work (PoW) require significant processing power, which other protocols like Proof of Stake are significantly more energy efficient, while as transactions are authenticated not by the number of computational resources but by the number of digital assets one owns. These techniques reduce energy use and encourage greater involvement and sustainability in the network. In addition to cryptographic primitives, mathematical primitives, such as error-correcting codes, are used to protect blockchain data both in transit and in storage against either accidental corruption or intentional malicious attacks. The idea of game theory is also used to understand the behaviour of participants in decentralized networks, hence promoting cooperation and discouraging fraudulent actions. Homomorphic encryption techniques allow computation of encrypted data without revealing sensitive information and, therefore, improve privacy in blockchain-based systems. In the modern digital world that is highly dependent on data, there has been a sharp rise in the issue of data privacy, data security, and data trust. Data breaches and cyberattacks are a threat of serious concern to both individuals and organizations. As a result, cybersecurity has become an essential factor in the context of the contemporary digital realm, whether it is internet banking and cloud computing or digital communication platforms. The security of confidentiality, integrity, and authentication of digital information is based on cryptography. In its simplest form, cryptography is based on fields of mathematics, including number theory, algebra, probability, and discrete mathematics. These basic principles are the cornerstones of safe communication networks and online technologies. Therefore, mathematics is not only an abstract endeavour but also a practical tool that enables safe digital transformation. The paper will aim at exploring the connections between mathematics, cryptography, blockchain technology, and cybersecurity. It explains the role played by mathematical concepts in ensuring safe information processing, privacy-sensitive communication, and decentralized transaction systems. The better comprehension of these connections can prepare researchers, developers, and educators to understand the practical value of mathematics in the new digital technologies and come up with more relevant solutions for a safer, data-driven world.
The digital money world is facing a massive security challenge. We have Decentralized Finance (DeFi), built on Smart Contracts-which are supposed to be self-executing and unbreakable-running on top of Cloud Computing, which is fast, scalable, but inherently centralized and has a big, easy-to-hit security perimeter. This awkward partnership creates a critical weak point. Hackers aren't breaking the blockchain itself; they are exploiting the connections, like manipulating data feeds (Oracles) or stealing cloud credentials, something old, siloed security checks simply miss. We've developed the Integrated Cloud-DeFi Resilience (ICDR) Framework to fix this. Think of it as a single, smart security bodyguard that protects your system from the cloud down to the code. The ICDR Framework seamlessly brings together three crucial defense layers: first, we automatically audit the Smart Contract code before it even launches; second, we use Cloud Security Posture Management (CSPM) to continuously monitor the cloud infrastructure’s health in real-time; and third, we use specialized Blockchain Technology (DLT) to create an unchangeable, honest record of every security event. The core innovation is its ability to play detective: it catches stealthy attacks by connecting a suspicious administrative action in the cloud (like a key change) with an immediate, shady transaction on the DeFi chain. In our tests on a simulated financial application, this unified approach reduced the time a system was vulnerable (Vulnerability Exposure Rate, or VER) by over 80% compared to separate monitoring tools. The ICDR Framework offers a crucial, practical model for the financial industry to build the resilient, compliant, and trustworthy digital banking systems of tomorrow. Keyword: Security Auditing; Decentralized Finance (DeFi), Smart Contracts, Cloud Computing, Cloud Security Posture Management (CSPM), Oracle Manipulation,Interoperability Risks, Cross-Stack Correlation, Immutable Audit Trail.
The fast evolution of large-scale Internet of Things (IoT) networks has made it possible to develop intelligent applications in smart cities, healthcare, industry automation, transport, and nextgeneration communication systems. However, the conventional centralized architecture and security mechanisms are seriously challenged regarding scalability, latency, energy efficiency, trust management, and resilience against cyber-attacks in large-scale and heterogeneous IoT networks.Blockchain and Distributed Ledger Technologies (DLTs) provide promising solutions with the help of decentralization, immutability, and secure data sharing. However, the conventional consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) are not appropriate for large-scale IoT networks because of their high computational and communication complexities. This review provides a comprehensive analysis of the latest blockchain-based IoT solutions, with emphasis on lightweight, scalable, and energy-efficient consensus algorithms for largescale IoT networks. The latest and most advanced consensus algorithms, such as Delegated Proof of Stake (DPoS), Practical Byzantine Fault Tolerance (PBFT) variants, sharding-based systems, Directed Acyclic Graph (DAG)-based blockchain solutions, and agent-based DLT systems, are analyzed. The peer-reviewed literature is analyzed using quantitative performance analysis criteria such as throughput, latency, scalability, energy efficiency, and security resilience. The results show that although the new emerging lightweight and distributed ledger architectures have shown substantial improvements in performance and scalability in large-scale IoT networks, there are still important research challenges to be addressed in security robustness, interoperability, real-time processing, and real-world deployment validation. The research gaps are identified, and future research directions are presented in this review to develop new lightweight, secure, adaptive, and scalable blockchain-based architectures for next-generation large-scale IoT networks.
Aman Chaudhary, Bhavy Singhal, Aryan Siwach, Priyanka Dhanraj
Abstract The rapid increase in digital data has led to heavy reliance on centralized cloud computing. Consequently, users are exposed to critical vulnerabilities, including unauthorized access, privacy invasion, and single points of failure. This study proposes a cloud storage system that is trustless to address these challenges that have persisted. The underlying methodology utilizes distributed data hosting based on the InterPlanetary File System (IPFS) and decentralized access control through Solidity smart contracts. Under this architecture, file metadata is stored safely on an unalterable blockchain registry, and the media files are stored off-chain. These contracts are automatically run by granular access controls like specific public and private visibility modes. At any point, no outside intervention of a third party is needed. The system was checked during the testing time in terms of a functional accuracy in regards to a secure storage, verifiable retrieval, and instant revocation of permissions. According to the key results, the elimination of intermediary control, prevention of unauthorized access to data attempts, and high data availability are achieved. In conclusion, this shows that a combination of programmable smart contracts and peer-to-peer storage will provide a potentially scalable and secure alternative to the traditional cloud architecture. This leads to a considerable improvement in user data sovereignty and systemic resilience as a whole. Keywords Ethereum, Solidity, IPFS, Smart Contracts, Decentralized Storage
ABSTRACT Forgery of academic and professional certificates remains a major concern across institutions. Traditional centralized systems are prone to manipulation and single points of failure. This work presents a blockchain-based certificate issuance and verification platform developed using Spring Boot and the Ethereum Sepolia test network. The system supports multiple organizations where issuers register and are approved by an administrator before generating certificates. Each certificate is assigned a unique identifier, and a SHA-256 hash of its data is stored on the blockchain through smart contracts. The platform also automates PDF certificate creation with embedded QR codes and sends them via email. Additional features include bulk certificate generation, revocation support, and public verification without requiring a blockchain wallet. Experimental observations indicate an average issuance time of around 4 seconds and verification within 1.5 seconds. Keywords: Blockchain, Ethereum, Smart Contracts, SHA-256, Certificate Verification, Spring Boot, Web3j, PDF Automation
<sec> <title>BACKGROUND</title> Self-sovereign identity (SSI) provides a decentralized approach to digital identity management, enabling individuals to control their personal data without reliance on centralized authorities. Blockchain technology offers a tamper-resistant and distributed infrastructure that can support secure and verifiable identity systems. In health care, where identity fragmentation, privacy risks, and interoperability challenges persist, blockchain-enabled SSI (BC-SSI) has been proposed as a potential solution. However, existing research remains heterogeneous, with varying levels of technical maturity and limited evidence of real-world deployment. </sec> <sec> <title>OBJECTIVE</title> This study conducts a scoping review to systematically map BC-SSI applications in health care and to analyze their application domains, development stages, study aims, targeted challenges, and technological infrastructures. In addition, this study aims to identify structural gaps in current research and assess the readiness of BC-SSI systems for clinical deployment. </sec> <sec> <title>METHODS</title> This review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) methodology. A comprehensive literature search conducted between September 2024 and August 2025 identified 37 peer-reviewed studies that met predefined inclusion criteria. Data were extracted and synthesized using descriptive and thematic analyses across application areas, system maturity, technological components, and reported challenges. </sec> <sec> <title>RESULTS</title> The findings indicate that BC-SSI research in health care remains at an early stage of maturity, with most studies proposing conceptual models or prototype implementations and limited real-world validation. Applications predominantly focus on identity verification, credential management, and privacy-preserving data exchange across domains such as electronic health records, mobile health, and access control systems. Commonly used technologies include decentralized identifiers, verifiable credentials, smart contracts, and privacy-enhancing mechanisms such as zero-knowledge proofs and selective disclosure. Despite rapid technical development, persistent challenges include interoperability limitations, governance gaps, usability concerns, and insufficient integration with health care infrastructures. Notably, a structural gap was identified between technological capability and system-level readiness for clinical deployment. </sec> <sec> <title>CONCLUSIONS</title> BC-SSI technologies demonstrate potential for enabling secure, interoperable, and patient-centric identity management in health care. However, current research is predominantly technology-driven and lacks sufficient system-level validation. This study highlights the need for integrated architectural approaches, governance frameworks, and real-world evaluation to bridge the gap between conceptual innovation and clinical implementation. Advancing BC-SSI toward health care adoption will require coordinated progress across technical, organizational, and regulatory dimensions. </sec>
Rajkishor Yadav, Preeti Yadav, K C Nithin Kumar, Vinay Kumar · 5 authors
The rapid enhancement in the use of Internet of Things (IoT) devices has introduced the issues viz privacy, scalability, and computational efficiency. Conventional blockchain solutions only provide decentralization and security. But they result in significant overhead and hence, not found suitable for resource-constrained IoT environments. This work proposes ZK-EdgeChain, an edge-assisted blockchain framework by integrating the lightweight Zero Knowledge Proofs (ZKPs) with edge computing to enable privacy preserving and scalable IoT system. The proposed framework offloads computationally intensive proof generation and verification to edge nodes while maintaining decentralized trust through blockchain. The paper also presents a formal mathematical model and optimized verification algorithm. The results validate a 75% reduction in communication overhead and 44% reduction in energy consumption compared to traditional approaches. The results demonstrate that the ZK-EdgeChain significantly improves efficiency, scalability, and privacy preservation in IoT networks.
Currently blockchain platforms are not capable of managing sufficient transactions per second. And the gas fees? They make most real world scenarios essentially infeasible. We built Ledgerlink Both these bottlenecks can be linked together, using Ethereum. smart contracts with Arbitrum’s Layer-2 rollup mechanism. Hashing coupled with cryptography and consensus engine (supports both). PoW and POS) eliminate changes in the data. L2 part provides throughput of the order of 10x that of mainnet. you, gas prices are less than 90% lower. Tech stack wise – Solidity. TypeScript, Express, and Next.js TypeScript, optimally backend with express, next as a whole. Frontend tailwind. Simulated load tests were carried out. Enterprise-grade volumes, which promote volumes, are. and can be accomplished without the latency and cost nightmares that you will normally. see on Layer-1. In the present paper we are going to walk through our architecture, the decisions that we made on the way (some good, some we’d) re- consider, and the benchmarking deliverables.
Abstract Federated learning (FL) has emerged as a paradigm-shifting approach to distributed machine learning, enabling multiple participants to collaboratively train models without exposing raw data. However, conventional federated learning architectures remain susceptible to a broad spectrum of security and privacy threats, including model poisoning, gradient inversion, inference attacks, and Byzantine faults. This paper presents a unified and robust framework— Secure and Privacy-Preserving Federated AI (SPFA) — that integrates differential privacy, homomorphic encryption, secure multi-party computation, Byzantine fault tolerance, and zero-knowledge proofs into a unified, production-grade architecture. We formally analyze the threat model, prove privacy guarantees under the ( ε , δ )-differential privacy framework, and demonstrate Byzantine resilience under partial adversarial participation. Extensive experiments on heterogeneous data distributions across image classification, natural language processing, and medical diagnosis benchmarks demonstrate that SPFA achieves model accuracy within 2.3% of centralized baselines while providing provable ε = 1.0 privacy with a communication overhead of only 18% above standard FedAvg. To the best of our knowledge, our framework is among the first to consolidate all five protection layers into a unified, deployable system with formal analysis and an open-source reference implementation. The relevance of SPFA extends to privacy-sensitive applications in healthcare, cybersecurity, distributed edge computing, and smart city analytics.
Agentic AI systems act at machine speed, yet the governance mechanisms meant to oversee them remain manual, reactive, and architecturally entangled with the systems they govern. The frontier problem is not capability; it is governability at runtime. This paper presents the complete architectural specification for the Governance Twin: a structurally independent, real-time governance system that shadows agentic AI operations without sharing code, memory, or direct communication channels. We introduce a three-plane architecture (Operational, Governance, Integrity) connected by strictly unidirectional data flows that enforce a fundamental separation: observation flows upward and is immutable, while guidance flows downward and influences agent context without controlling agent execution. Within this architecture, we specify four novel components and their interactions. Sentinels perform external-only behavioral observation, comparing agent actions against a governance baseline and packaging deviations into Evidence Bundles, the atomic unit of governance memory. A multi-agent Council aggregates evidence across the agent population, detects emergent patterns through statistical and correlation analysis, and reaches governance decisions via structured voting with delegated authority boundaries. The Historian maintains governance memory across three specialized stores (graph, vector, and append-only) to support provenance traversal, semantic precedent search, and sequential audit. An Ethics-Morals-Values (EMV) state hierarchy governs behavioral expectations at three levels of stability, from hard boundaries that change over months to adaptive thresholds that tune continuously. Integrity is achieved through hash chains, Merkle trees, and distributed ledger anchoring that make tampering detectable rather than claiming to make it impossible. The architecture is platform-independent, specifying capability requirements rather than vendor products, and is designed for incremental adoption from single-agent deployments to federated multi-organization governance. All design decisions are grounded in the principle that governance must operate at the same speed as the systems it governs, while remaining structurally incapable of becoming an operational bottleneck.
Blockchain technology has become a game-changing way to solve long-standing problems with data security, integrity, and trust in distributed environments. Its decentralized structure, unchangeability, and cryptographic features make it a strong way to protect sensitive data from unauthorized access, tampering, and cyberattacks. This study investigates the function of blockchain in fortifying contemporary data security frameworks, analyzing the ways in which consensus algorithms, smart contracts, and distributed ledgers improve confidentiality, availability, and accountability. This study emphasizes blockchain's capacity to transform data governance through an in-depth examination of existing applications, limitations, and case studies, while also identifying the technical and operational challenges that must be resolved for widespread implementation. This study also highlights the role of the CoreDaoVip Global Curriculum in strengthening blockchain-based data security frameworks by integrating decentralization, cryptographic mechanisms, smart contracts, and ethical governance. The curriculum adopts a security-by-design approach aligned with the Satoshi 3.0 philosophy, enabling the development of tamper-resistant, transparent, and privacy-preserving data architectures. By bridging theoretical foundations with practical implementation, CoreDaoVip prepares a globally competent workforce capable of addressing emerging data security challenges across critical digital ecosystems.
In this paper, they speak of the evidence protection system (EPS) that is a new approach to problem resolution involving contemporary legal and investigative procedures. The EPS uses the blockchain technology called Ethereum to ensure that under all the stages of the evidences life-cycle they are secured, authentic and comprehensive. Using timestamps, smart contracts, and cryptography sequencing, the system creates an evidence management platform, which is easy to read, decentralized, and cannot be hacked. The EPS stores evidence as a record that is not mutable through the use of distributed ledger technologies and digital timestamps. This is what makes it be safer than the centralized systems. smart contracts even the playing field of security and transparency by providing automation of functions such as chain of custody and access control. The integrity of data can be checked in two ways, encryption, and hashing, and keep the actual data safe. overall: the EPS provides the full solution to the issues of processing the evidence in legal environment of the current times, which is why confidence in the efficiency and credibility of evidence that is stored grows.
The explosion of multimodal healthcare data such as medical images, physiological signals, and electronic health records has posed major security storage problems, credible data sharing, and correct disease diagnosis. Traditional healthcare is usually vulnerable to privacy concerns, unauthorized access, and poor analytic abilities. To handle the above challenges, this paper suggests STMD-BTNet, an intelligent and secure architecture that combines blockchain-based trust management and deep neural networks to process multimodal healthcare data reliably. The proposed system secures patient data with a dynamic hash-based session key generation system and secures the transmission with a verified blockchain bridge that uses a trust-conscious Proof-of-Stake consensus system. Access control with smart contracts can be used to provide access to sensitive records by authorized medical professionals. A multimodal deep learning model that incorporates convolutional neural networks to process medical images, long short-term memory networks to process physiological signals, and fusion layer to combine features of clinical attributes allows patients to receive the correct diagnosis. Experimental results on publicly accessible healthcare datasets show better performance with accuracy of 98.62, precision of 98.45, recall of 98.30 and AUC of 99.12 in the combined application of the multimodal, and low latency and improved data security. Comparative analysis has proved that STMD-BTNet is more reliable to diagnose, scale, and trust well than current deep learning and blockchain-based methods and is therefore applicable in next-generation intelligent healthcare infrastructures.
This paper proposes the design and evaluation of a secure electronic payment system based on the Ethereum blockchain, applied to the payment of academic fees. The objective is to enhance transparency, security, and automation of financial transactions within higher education institutions. The methodology relies on developing a prototype using smart contracts, tested on Ethereum testnets. Experimental results show that the system reduces processing times and improves transaction traceability [1]. The integration of Layer 2 solutions and stablecoins also helps reduce transaction costs and improve scalability. However, challenges remain, particularly regarding regulation and user accessibility. As a decentralized and programmable platform, Ethereum represents a major innovation capable of transforming traditional payment systems. The emergence of Ethereum-based academic fee payment systems is part of an accelerated digital transformation and the search for alternatives to conventional financial infrastructures. Since the introduction of Bitcoin, the global financial system has undergone a profound shift, marked by the adoption of decentralized technologies [3]. This study required an in-depth technical understanding of the Ethereum blockchain, along with critical, economic, and regulatory analyses [5].
Blockchain-Driven Healthcare Platform with Access-Controlled Record Management is a decentralized application designed to enhance the security, privacy, and accessibility of medical records. Traditional healthcare systems rely on centralized storage, making sensitive patient data vulnerable to breaches, manipulation, and unauthorized access. This project utilizes blockchain technology to provide a secure and tamper-proof environment for storing and managing healthcare data. Smart contracts are implemented to enforce access control, allowing patients to grant or revoke permission to doctors and healthcare providers. Medical records are securely stored using decentralized storage mechanisms, while blockchain maintains immutable references to ensure data integrity. The platform integrates Web3 technologies for secure user authentication and seamless interaction with the blockchain network. By eliminating intermediaries, the system improves transparency and trust among stakeholders. This solution demonstrates an efficient approach to managing healthcare data, ensuring confidentiality, integrity, and availability while addressing the limitations of traditional healthcare record systems in a modern, digital environment.