Blockchain technology has emerged as one of the most transformative innovations of the 21st century, fundamentally reshaping how digital transactions are recorded, verified, and secured across distributed networks without centralized intermediaries. Originally conceived by Satoshi Nakamoto in 2008 as the underlying architecture for Bitcoin, blockchain has evolved far beyond cryptocurrency applications to encompass smart contracts, decentralized finance, supply chain management, healthcare systems, and enterprise solutions. This comprehensive review provides an accessible yet thorough examination of blockchain technology, targeting readers from beginner to intermediate levels seeking to understand both theoretical foundations and practical implementations. We systematically explore the foundational principles of blockchain architecture, including distributed ledger technology, block structure and chain formation, Merkle tree organization, and peer-to-peer network topologies. The paper provides in-depth analysis of cryptographic primitives including hash functions, public-key cryptography, elliptic curve digital signatures, and emerging quantum-resistant approaches. We examine diverse consensus mechanisms ranging from proof-of-work to proof-of-stake variants, Byzantine fault tolerance protocols, and hybrid approaches, analyzing their trade-offs in security, decentralization, and performance. The review extensively covers smart contract platforms with emphasis on Ethereum's architecture, vulnerability patterns, and security best practices. Critical scalability challenges are addressed through examination of layer-two solutions including Lightning Network, state channels, rollups, and sharding protocols. We analyze security threats across network, consensus, and application layers, alongside privacy-enhancing technologies such as zeroknowledge proofs and confidential transactions. Real-world applications are explored across financial services, supply chain management, healthcare, Internet of Things, and digital identity systems. The paper examines enterprise blockchain frameworks, particularly Hyperledger Fabric's permissioned architecture, comparing public and private blockchain tradeoffs. Finally, we discuss current challenges including energy consumption, regulatory uncertainty, and interoperability limitations, while exploring future research directions in quantum resistance and cross-chain protocols. By synthesizing insights from 75 peer-reviewed sources spanning foundational research, recent advances, and practical implementations, this review serves as a comprehensive resource for researchers, practitioners, and students seeking to understand blockchain technology's current state and transformative potential.
Rapid digital transformation across financial, e-commerce, and decentralized platforms has amplified the need for secure, transparent, and resilient transaction systems. Conventional security mechanisms often fail to address sophisticated cyber threats, identity fraud, and evolving attack patterns, highlighting the necessity for integrated technological solutions. The convergence of Blockchain and Artificial Intelligence (AI) establishes a robust framework that combines immutable, decentralized ledger structures with adaptive, intelligent analytics. Blockchain ensures transactional integrity, data provenance, and decentralized trust, while AI facilitates real-time anomaly detection, predictive risk scoring, and automated decision-making. This synergy enhances digital identity management, strengthens access control, and mitigates fraud by enabling continuous monitoring, behavioral analysis, and transparent verification processes. Applications extend to secure payments, smart contracts, cross-border transactions, and decentralized finance ecosystems, demonstrating improved operational efficiency, scalability, and resilience. The chapter also explores privacy-preserving computation, federated learning, and explainable AI frameworks to ensure ethical and accountable deployment of intelligent transaction systems. By integrating structural security with predictive intelligence, Blockchain-aided AI frameworks establish a next-generation foundation for secure digital transactions, fostering trust, regulatory compliance, and systemic reliability across global digital networks.
Ashwag Alotaibi, Huda Aldawghan, M. M. Hafizur Rahman
This study summarizes the body of research on the IoT and NFTs overlap, highlighting important security concerns, the function of blockchain technology, and implications for future study and smart environment applications. IoT devices provide creative solutions that boost operational effectiveness and enhance user experiences as they spread throughout different sectors. But there are also serious drawbacks to this expansion, especially in terms of security and privacy. At the same time, NFTs unique digital assets verified by blockchain technology—have become extremely popular because of their unique features and wide range of uses. This paper carefully looks at how security frameworks in digital ecosystems may be impacted by the integration of IoT and NFTs. The results emphasize how urgently this integration must be studied further to minimize new risks and maximize the advantages of IoT and NFTs across a variety of sectors. The study intends to contribute to a more secure and effective IoT ecosystem by examining the difficulties presented by this integration. Contributing to the development of a more robust and secure IoT ecosystem is the ultimate aim of this research. This study aims to open the door for future developments that optimize the benefits between the two technologies while reducing risks by recognizing and evaluating the difficulties brought about by the integration of IoT and NFTs. Both academics and industry stakeholders navigating the rapidly changing IoT and blockchain world will find great significance in the results of this research.
Accounting is undergoing a radical transformation due to the integration of traditional information systems with blockchain technology and artificial intelligence. Openness, automation, and smart decision-making will all become a reality via this connection. However, traditional SAIS are typically centralized and do not inherently include blockchain or AI. In this study, Smart Accounting Information System (SAIS) technologies are redefined through the integration of these technologies to enhance transparency, automation, and real-time assurance. Blockchain technology's immutability, traceability, and AI's ability to recognize abnormalities and predict provide a more intelligent and secure auditing process. Conventional accounting methods have several issues, including delayed audits, lack of transparency, fraud, and human mistakes. Existing systems fail to provide intelligent anomaly detection and real-time transaction traceability. Financial reporting and audits need immutable records and proactive analytics. There is an urgent need for a single framework to ensure this requirement and its quick implementation. This study proposes the collaborative blockchain-AI audit trails method (CBAATM) for Smart Accounting Information Systems. This is done due to the difficulties mentioned. AI-powered modules utilize fuzzy inference to dynamically analyze audit risks and Random Forest classifiers to detect real-time fraud. This research project utilizes zero-knowledge proofs and homomorphic encryption to simultaneously handle data aggregation, privacy, and independent audits. Using middleware application programming interfaces makes integration with ERP and AIS systems easy. Throughout the testing process, the model outperforms conventional audits. The methodology, according to statistical research, ensures the detection accuracy ratio of 95%, integrity of the blockchain 99.2% of the time, identifies abnormalities 94.1% of the time, satisfies compliance standards 95.4% of the time, and reduces audit latency by 41.5% compared to other existing models.
<p>The rapid evolution of decentralized finance (DeFi) has brought revolutionary innovations to global financial systems; however, it has also revealed some major security vulnerabilities, especially of smart contracts. Traditional auditing methods and static analysis tools are prone to fail in identifying sophisticated threats, including reentrancy attacks, front-running, oracle manipulation, and honeypots. This review discusses the growing role of machine learning (ML) in enhancing the security of DeFi systems. It provides a comprehensive overview of modern ML-based methods related to the detection of smart contract vulnerabilities, transaction-level fraud detection, and oracle trust assessment. The paper also provides publicly available datasets, necessary toolkits, and architectural designs used for developing and testing these models. Additionally, it provides future directions like federated learning, explainable AI, real-time mempool inspection, and cross-chain intelligence sharing. While it is full of promise, the application of ML in DeFi security is plagued by issues like data scarcity, interoperability, and explainability. This paper concludes by highlighting the need for standardised benchmarks, shared data initiatives, and the integration of ML into development pipelines to deliver secure, scalable, and reliable DeFi ecosystems.</p>
Abstract The demand for secure, effective, and scalable payment systems has increased due to the rise of Internet-based financial transactions. Through traditional techniques, such as Proof of Work (PoW), conventional financial systems often encounter issues with high transaction latency, concerns about fraud, and excessive energy consumption. These problems are widespread in traditional systems. This research proposes a Secure Hybrid Consensus Protocol (SHCP) with the intention of enhancing the effectiveness, velocity, and reliability of financial transactions based on Blockchain technology. The Proof of Stake (PoS) protocol is combined with the Byzantine Fault Tolerance (BFT) protocol by SHCP. Through the utilization of adaptive prioritization, Bayesian inference, and anomaly recognition, SHCP can incorporate the most advanced fraud detection technology. The SHCP framework uses anomaly recognition to identify fraud with 92% accuracy, 38% faster validation, and 43% less energy than PoW-based systems. The system delivers ~ 7,000 TPS (Transactions Per Second) and a 27% increase in decision risk prediction stability. Anomaly scoring, Bayesian inference, and adaptive prioritization aid fraud detection. These advances enable safe, rapid, and affordable financial transactions, creating a sustainable Blockchain-based payment ecosystem.
Abstract In today’s world, most financial and personal transactions happen online. This makes data security a big concern. To address risks like data breaches, hacking, and identity theft, our project “Blockchain Secure Transaction” aims to create a dependable and decentralized system for secure digital payments. The system uses blockchain technology to ensure transparency and immutability in each transaction, eliminating the need for a central authority. The process starts with user registration, where details are securely stored along with a picture password for better recognition. During login, users must pass both the picture password and a biometric check. This ensures that only the account. Once verified, the user enters the dashboard, where transactions begin through Zero-Knowledge Proof (ZKP) for privacy-preserving verification. Every transaction is validated with smart contracts. If there’s any mismatch or automatically blocks or freezes the transaction. The backend uses Java, while Firebase stores user data securely, and 2 factor.in enables OTP-based authentication. The frontend interface, designed in React (app.jsx), allows smooth navigation across pages. By combining blockchain, smart contracts, biometric authentication, and ZKP, this project provides a secure and user-friendly platform that prevents unauthorized access and builds user trust in digital payment systems Keywords Blockchain, Secure Transaction, Zero Knowledge Proof (ZKP),Smart Contract, Biometric Authentication, Picture Password, Decentralized System, Data Privacy, Transaction Verification, Firebase Integration, 2 factor.in OTP Authentication.
The rapid evolution of cyber threats has exposed fundamental weaknesses in traditional intrusion detection systems, particularly those dependent on centralized architectures vulnerable to data tampering, single-point failures, and delayed threat response. As organizations face increasingly sophisticated attacks, a resilient and transparent framework for detecting and validating abnormal activity has become essential. This study examines the design and effectiveness of a blockchain-based intrusion detection system (BIDS) that leverages distributed consensus, immutable logging, and cooperative threat intelligence to enhance the reliability and responsiveness of security operations. By integrating blockchain technology with anomaly-based and signature-based identification methods, the proposed model establishes a secure environment where intrusion data cannot be altered, suppressed, or manipulated by internal or external adversaries. Through experimental evaluation across simulated network environments, the blockchain-enabled detection model demonstrates significant improvements in event accuracy, traceability, and coordination between participating nodes. The decentralized ledger structure ensures that alerts are validated collectively, reducing false positives and limiting the adversary’s ability to compromise the detection process. The integrity of recorded events also enhances forensic analysis, allowing security teams to reconstruct attack sequences with greater confidence. Additionally, the study reveals that the distributed nature of the system provides high fault tolerance, enabling continuous operation even under attempted denial-of-service conditions or node outages. Performance analysis indicates that blockchain integration does introduce additional computational overhead; however, the trade-off is compensated by the increased transparency, data authenticity, and resistance to insider threats that the system delivers. The research further highlights that smart contracts can automate rule enforcement and improve response mechanisms by triggering protective actions when predefined thresholds are met. This automation contributes to shortening detection-to-response timelines, a critical factor in mitigating fast-moving cyberattacks. Overall, the findings suggest that blockchain-powered intrusion detection represents a promising direction for strengthening network security in decentralized, cloud-based, and large-scale enterprise environments. By combining autonomous threat identification with tamper-proof logging and distributed validation, the proposed approach offers a comprehensive pathway for defending modern digital infrastructures against evolving cyber risks. The study concludes that integrating blockchain technology with intrusion detection principles not only reinforces system resilience but also lays the groundwork for more collaborative, transparent, and secure cybersecurity ecosystems.
The study is grounded on the significant shifts, central values, and increased influence of Blockchain Technology on the industries. It addresses Blockchain Technology starting theoretically as a cryptographic concept of the beginning through to its contribution as a primarycomponent of decentralized computing (Web3). The discussion begins as the key issues are examined, namely, decentralized agreement, cryptographic hashing, and immutability. Such subjects enable the Blockchain Technology to gain trust in cases where mediators were being used in the past. Moreover, the research considers the impacts of Blockchain Technology on such critical industries as Decentralized Finance (DeFi), supply chain management, and decentralized governance (DAOs).
Dileep Kumar Murala, Shadab Ahmad, V. A. Sankar Ponnapalli, Veera Ankalu Vuyyuru · 5 authors
Wireless sensor networks (WSNs) will be necessary for the next generation of Internet of Things (IoT) apps. They make it possible to use smart and long-lasting sensors and smart automation in healthcare, Industry 4.0, and critical infrastructure. But security is particularly hard since they have built-in flaws, not enough computer power, not enough energy, and a significant danger of insider threats. Standard encryption methods aren't enough, and in situations where resources are restricted, heavier blockchain or machine learning solutions aren't always possible. This study presents ChainShieldML, a lightweight hybrid security architecture that combines Blockchain (BC) and machine learning (ML) to provide decentralised, adaptive, and resource-efficient protection for wireless sensor networks (WSNs). The idea is based on a two-pronged defence strategy. The Blockchain Prevention Module's permissionless blockchain architecture for base stations and cluster heads makes it possible to verify identities, maintain trust in a decentralised way, and keep node interactions unchangeable. Smart contracts made in solidity and connected to the Ethereum ecosystem make it possible to safely register nodes and keep an eye on what they do. The VBFT consensus algorithm makes it possible to quickly validate without using as much computing power as most proof of work methods. The machine learning detection module uses the lightweight gradient boosting method (LightGBM) to find and rank dangerous nodes in real time. LightGBM is the best machine learning classifier when looking at things like recall, F1-score, Matthews correlation coefficient, training cost, and inference latency. ChainShieldML dramatically improves the detection of insider attacks, builds trust, and protects data while using very little energy and having very little communication delay, as shown in tests. For Wireless sensor networks (WSNs) to keep working, all of these things are very important. ChainShieldML is a novel solution to keep IoT devices safe. It uses blockchain's decentralised trust and ML's adaptive intelligence to make a defence system for next-generation wireless sensor networks that can grow, is strong, and is ready for the future.
Blockchain has become peer-to-peer immutable distributed ledger technology network, and its consensus protocol is essential to the management of decentralized data. The consensus algorithm, at core of blockchain technology (BCT), has direct impact on blockchain's security, stability, decentralization, and many other crucial features. A key problem in development of blockchain applications is selecting the right consensus algorithm for various scenarios. Ensuring scalability is the most significant drawback of BCT. The industry has been rejuvenated and new architectures have been sparked by the usage of consensus protocols for blockchains(BC). Researchers analyzed shortcomings of proof of work (PoW) consensus process and subsequently, alternative protocols like proof of stake (PoS) arose. PoS, together with other improvements, lowers the unimaginably high energy usage of PoW, making it protocol of time. In PoS, only the user with highest stake becomes the validator. To overcome this, we propose Scalable Proof of Stake (SPoS), a novel consensus protocol, which is an enhancement of PoS protocol. In the proposed algorithm, each stakeholder based on the stake gets a chance to become the validator and can mine blocks in the blockchain. Clustering of the stakeholders is done using mean shift algorithm. Each cluster gets a different number of blocks to mine in BC. Cluster with highest stake will get a greater number of blocks to mine when compared to other groups and the cluster with the least stake gets least number of blocks to mine when compared to other groups. To mine the blocks, validator is chosen based on the cluster in which he is present. Fair mining is ensured for all stakeholders based on number of stakes. Mining is distributed among all the stakeholders. Since the validators are chosen fast, the transaction rate is high in the network. Validators in PoS are selected according to the quantity of cryptocurrency they stake. More stakeholders will get chance of validating blocks and receiving rewards. Over time, this reduces fairness and decentralization by concentrating on wealth and power. This is addressed in SPoS using clustering-based validator assignment.
Blockchain is the new age internet equivalent evolution along with the rise of artificial intelligence they both are revolutionizing a new way of safer, faster, and government free interaction for real time financial verification. This study primarily investigates the role of these new age technologies in providing better security and transparent transactions in accounting systems related to crypto notably in decentralized finance (DeFi) ecosystems currently prevailing on solana, Ethereum and Base networks. These blockchain networks currently power billions of transactions in value using great techniques to ensure immutable, verifiable audit trails while removing any 3rd party interference In 2025 major accounting firms and compliance institutions will use AI-driven analytics, anomaly detection and predictive modelling to provide much better scope and structure of audit; this will help to decrease human errors and compliance delays by an estimate of 30%. AI along with blockchain technologies will provide real time decentralized monitoring and forensic analysis via smart contracts with include the major one such as ERC-20The combination of blockchain’s immutable ledger and AIs supremely adaptive intelligence creates a new wave of real time auditing right from retrospective verification to predictive ongoing assurance. However due to delays and legislative fragmentation issues and government ethical remain major obstacles for successful development. Finally our study demonstrates that the combination of Al with blockchain marks a fundamental change toward transparent, automated, and resilient accounting ecosystems capable of maintaining confidence in an increasingly digital and decentralized global economy.
Open access
2 source records
Blockchain Technology Applications and Security
Internet of Things and AI
Innovations and Analysis in Business and Education
Ra’ed Fawzi Aburoub, Nabeel Mahdi Althabhawi, Mohamad Rizal Abd Rahman, Ammar Abbas Kadhim
This paper explores the lifecycle of a smart contract, from the stages of coding and deployment to execution and verification, in order to show that a smart contract can indeed be self-executing, transparent, and immutable. While such functionalities introduce efficiency, trust, and reliability within industries such as financial, supply chain management, and health sectors, smart contracts at the same time have a host of technical and legal challenges arising. This paper identifies key issues: critical vulnerabilities in coding, deployment on immutable blockchains, address assignment complexities, triggering mechanisms, and aspects of privacy. This study has adopted a critical analytical approach to evaluate the technical and legal aspects of smart contract formation, complemented by inductive reasoning to derive general insights and recommendations from specific cases and patterns. The study states that the apt legal framework must be provided for liability, regulatory compliance, and solutions that would be unlooked-for. It further supports hybrid models that blend automation with human oversight, superior communication protocols regarding updating an address, and the use of technologies that allow transparency with the preservation of confidentiality in a balance. The concrete ideas it offers are attempts at technology design aligned with legal frameworks by bringing developers, regulators, and stakeholders together in implementing certain solutions. It emphasizes that continuous research will hence be important to assure reliability, security, and equitability in the adoption of smart contracts, expanding possibilities for their application in an increasingly changing digital environment.
Abstract Blockchain technology has become a transformative solution for secure and transparent digital ecosystems. This paper explores how decentralization, cryptographic hashing, distributed consensus, and immutable ledger architecture contribute to advanced data protection in the IT industry. The study integrates findings from existing literature, evaluates blockchain’s practical applications in sectors including finance, healthcare, supply chain, and governance, and examines a proposed multi-layer blockchain framework. The research highlights blockchain’s advantages in enhancing confidentiality, integrity, availability, and auditability, while identifying its limitations such as scalability, regulatory constraints, and environmental impact. Future scope emphasizes integration with AI, IoT, Web 3.0, quantum-resistant models, and cross-chain interoperability. Overall, the study concludes that blockchain is a critical technology for advancing trust-driven IT infrastructures. Keywords Blockchain, Data Security, Transparency, Decentralization, Smart Contracts, IT Industry
S Thillainayagi, Paolo Pavan, S Shashank, L V Preetham · 5 authors
Bitcoin is known for its high volatility and speculative trading behavior.Predicting Bitcoin prices is valuable for investors, traders, and financial analysts.The study uses historical price data, technical indicators, and/or sentiment analysis.Machine learning and statistical models like ARIMA, Linear Regression, and LSTM are applied.Deep learning models, especially LSTM, show better accuracy in capturing time-series patterns
Smart contracts automate blockchain transactions but are vulnerable to reentrancy attacks, where an attacker repeatedly calls a function before the contract updates its state, stealing funds. A well-known case is the 2016 DAO exploit, which caused a loss of $60 million.This study investigates methods to protect contracts from such attacks through a literature review, a case study comparing a vulnerable and a fixed contract, and evaluation of analysis tools (Mythril, Slither, Securify, Sereum, BlockWatchdog).The expected results include identifying effective coding patterns (like checks-effects-interactions and reentrancy guards), assessing tool accuracy, and providing secure development guidelines. All experiments will be conducted safely on test networks.
Blockchain technology has recently undergone substantial investigation into the prospect of integrating it with several service sectors, having originally been designed for the Peer-to-Peer cryptocurrency network, Bitcoin Database security could be an expensive and time-consuming operation. When discussing a legally binding contract, the phrase "automated transaction protocol that, executes the terms of the agreement" is used. The Internet of Things (IoT), big data artificial intelligence technologies, and blockchain technology into the supply chain may help solve the transparency and traceability issue stated in the literature.
The Internet of Things (IoT) generates massive volumes of patient and healthcare data every day. Providing the required accuracy for data classification, processing time, and analyzing the vast volumes of data from IoT devices and sensors are said to be the main challenges in IoT. Cloud computing is widely utilized as the foundation for the technologies required to secure healthcare. The healthcare industry has the most promise for blockchain technology since it can be used to integrate fragmented systems, the standard of electronic medical records should be raised, and take a more patient-centric approach to healthcare systems. The objective is to protect medical data, enable patients to use it to support their medical care, and provide reliable consent protocols for data exchange between various institutions and apps. Provide a blockchain-based architecture that verifies user identity using the Secure Hash Algorithm (SHA256) and Proof of Stake (POS) cryptography consensus technique to guarantee EHR sharing across many electronic healthcare systems.In this study, we assessed the performance of our proposed architecture using several metrics, and found that blockchain is a reliable security solution for the upcoming IoT network.
Prajakta Sudhir Khade, Aarushi Santosh Gode, Rajeshkumar U. Sambhe
The exponential rise of cyber threats has revealed the vulnerabilities of centralized security systems, including susceptibility to insider attacks, single points of failure, and regulatory inefficiencies. This paper investigates blockchain as a transformative backbone for cybersecurity, focusing on its potential to ensure data integrity, decentralize trust, and mitigate advanced cyber risks. Beginning with a comprehensive literature review, the study examines the fundamentals of blockchain technology—distributed ledgers, consensus mechanisms, and cryptographic primitives—that enable tamper-proof, transparent, and secure digital ecosystems. The challenges of centralized systems are contrasted with blockchain’s resilience, highlighting its role in eliminating bottlenecks and enhancing trust. Applications across identity management, IoT security, supply chains, and e-governance are analyzed alongside a proposed methodology that integrates blockchain with artificial intelligence, IoT, and quantum-resilient models. Real-world case studies demonstrate blockchain’s adoption in healthcare, government, and industrial systems, while challenges such as scalability, interoperability, and compliance are critically assessed. Collectively, this study underscores blockchain’s pivotal role in shaping next-generation cybersecurity architectures.
Shwetha K R, Divya G S, Bhavan Pande, Darshan K · 6 authors
Due to the ever-increasing demand to use safe and reliable electronic votes, a blockchain-based secure voting system has been developed to enhance transparency, trustfulness, and voter recognition. This system eliminates such issues as voting fraud, impersonation, and manipulating the results by means of biometric verification and decentralized blockchain ledger. The voters are matched to a facial-recognition database containing previously registered voters before voting. It is authenticated by a K-Nearest Neighbors (KNN) approach as it works well on classifying facial features and is not very laborious. After the vote is successfully authenticated, it is stored and signed on a blockchain network where it cannot be altered by another party. The features of smart contracts ensure the safety of voting, the correct counting of votes, and the awareness of each network node of what is happening. The cryptography of hashing and decentralized make certain that the votes are immutable, due to the decentralized structure of blockchain and consensus mechanisms. The face-matching module ensures that only the qualified individuals are allowed to vote. The system also supports mass elections and guarantees the ease of interaction among the voters. It was designed in such a way that it is scalable and user friendly. Trust, security, and efficiency are enhanced in the system through biometrical authentication, distributed ledger technology, encryption, and classification through machine-learning. It is highly dependable in how to conduct the current digital elections.
Since the introduction of Bitcoin in 2008, the blockchain technology as its underlying architecture, has attracted attention from various sides due to its decentralized and distributed computing characteristics. AS the core advantage of blockchain technology, the consensus mechanism determines various characteristics of blockchain, such as security, scalability, and decentralization. Currently, there are many consensus mechanisms suitable for different scenarios. This paper studies the existing consensus mechanisms from the perspectives of algorithm principles, performance, etc. Firstly, this article divides the existing consensus mechanisms into Proof of Work (PoW), Proof of Stake (PoS), and Byzantine Fault Tolerance (BFT). Secondly, for each type of consensus mechanisms, the study analyzes their algorithmic principles, understands typical solutions and latest ones, clarifies the advantages, disadvantages, and the possible attack methods of various consensus mechanisms. Finally, the paper defines the basic requirements for new consensus mechanisms. It aims to help break through the application bottlenecks of blockchain technology and promote the development of blockchain technology in various scenarios.
Blockchain technology is rapidly becoming one of the most groundbreaking technologies for revolutionizing supply chain management with unprecedented security, transparency, and efficiency. This paper presents a comprehensive literature review of blockchain and its applications in leading industries such as transportation, manufacturing, food and beverage, and healthcare. Blockchain applies distributed ledger technology to secure tamper-evident record-keeping, which significantly enhances traceability and provenance verification across complex supply chains. By integrating smart contracts, IoT connectivity, and decentralized financial services, blockchain can solve significant challenges, such as counterfeiting, supplier management, and enforcing sustainable and responsible sourcing practices. Despite these benefits, the mass-scale adoption of blockchain faces serious challenges, such as scalability, interoperability, regulatory ambiguity, and a lack of standardized frameworks. The report also addresses the environmental concerns of blockchain’s power-intensive proof-of-work algorithm and discusses ways to counteract them. Future developments in artificial intelligence and 5G networks will continue to evolve supply chain management in ways that unleash unmatched efficiency and potential.
Supply chain operations that include blockchain technology have the potential to improve cybersecurity and data integrity. The complexity and interconnectedness of global supply chains make it imperative to guarantee the security and validity of data for all parties involved. Because blockchain technology is decentralized, transparent, and unchangeable, it offers a perfect solution to common supply chain weaknesses, including fraud, data tampering, and illegal access. The use of blockchain technology to protect important data at each link in the supply chain—from manufacturing and procurement to distribution and delivery—is examined in this article. By leveraging smart contracts, cryptographic security, and distributed ledger systems, blockchain can ensure the traceability of goods, validate transactions, and protect sensitive information from cyber threats. The paper also highlights how blockchain has the potential to completely transform supply chain management security while addressing issues like scalability, integration with current systems, and regulatory considerations. In the end, this study highlights how blockchain technology may improve data integrity, lower cyber threats, and foster trust among supply chain actors.