More and more IoT use cases require trustworthy computing from cloud/back-end services, which cannot necessarily provide a fully trusted execution environment, data immutability, and traceability. The integration of IoT with the blockchain technology is one of the most promising solutions to achieve the previously mentioned features in the IoT networks. Researchers are also interested in integration solutions, and several solutions are already present in the scientific literature. However, there are still some uncertainties in establishing a direct and effective interaction between an IoT device and the given blockchain. In this work, we propose the first IoT hardware architecture model designed to accelerate time-consuming operations of IoT-Blockchain. The proposed IoT hardware architecture model is programmed in SystemC-TLM and can provide a significant reduction in execution time, 53% and 18% when running Hyperledger Sawtooth and Ethereum applications, respectively.
Jorge Peña Queralta, Farhad Keramat, Salma Salimi, Lei Fu · 6 authors
Abstract Purpose of Review: Distributed ledger technologies (DLTs), particularly blockchain, are paving the way to securing and managing distributed and large-scale systems of autonomous agents. We look into how these technologies are moving out of the lab and into the real world within the robotics field. Recent Findings: Despite the scalability and real-world applicability concerns, new solutions have emerged that show resilience to intermittent connectivity, as well as scalable solutions for managed or permissioned networks. Summary: We present a review on the various use cases that different DLTs can support in multi-robot systems. We argue that the majority of the work to date on open and permissionless blockchains is only applicable to a subset of robotics use cases, with novel DLT architectures and permissioned blockchains driving adoption across industrial and more mature application scenarios.
The Internet of Things (IoT) has expanded because of the development of information technology. IoT impacts several fields, including the medical profession, smart cities, and data management. The development of sustainable medical systems is significantly aided by the Internet of Medical Things (IoMT). IoMT has a big impact on healthcare since it makes it easier to monitor and validate data about patients before storing it in the cloud. Keeping all data confidential and secured is essential since the IoMT is a big-data platform that is expanding quickly.This paper will apply this technical advancement to the realm of health, namely e-health. The research provides an IoMT-based monitoring tool for personal health surveillance. Block chain technology may resolve present interoperability issues in health-related systems and offer technological solutions that allow the electronic transfer of medical records to medical organizations and medical specialists. However, the transmission and security of people's health data remain a major concern in IoMT devices across a wide range of product categories. This research uses block chain as a secure solution to satisfy the requirements of medical privacy and data security. In this study, a Block chain-based IoMT security System (BC-IoMT-SS) is presented based on BC technology in IoMT for the security, privacy, and management of patient information. The suggested framework is successfully implemented to fulfill the optimal privacy and safety criteria for medical data management in IoMT gadgets. Utilizing the block chain's key, a healthcare application system has been created in which the person's health data may safely generate alerts for verified healthcare practitioners. Simulation results demonstrate that the suggested BC-IoMT-SS technique produces a high precision ratio of 94%, an efficiency ratio of 94%, a shorter delay of 0.63s, and a shorter reaction time compared to other current methods.
IOTA is a new public chain system specifically designed for the Internet of Things (IoT), which provides strong support for the high concurrency, scalability, and zero handling fees of the IoT. The distributed ledger of IOTA, called the tangle, adopts a Directed Acyclic Graph (DAG) structure. However, compared to the single-chain architecture, the tangle is more complex and highly vulnerable to security threats. The existing transaction verification methods still cannot simultaneously meet the need for accelerating approval speed and improving security to resist illegal transactions, such as lazy tips and permanent tips. In this work, we propose TDTS, a tip-selection algorithm based on time division to improve the efficiency of transaction verification. The main idea of the algorithm is to quickly determine two tips of an incoming transaction that need to be confirmed by sorting tip values in a time slot. It shortens the transaction verification time and reduces the number of lazy tips and permanent tips. A comprehensive theoretical analysis confirmed the effectiveness of our proposed algorithm. Based on 1000 IOTA nodes, the evaluations showed that TDTS can select tips quickly like URTS and resist lazy tips like MCMC.
The integration of fog computing and blockchain in the Internet of Medical Things (IoMT) domain has wholly transformed the healthcare industry and e-health services. In IoMT, the patient’s personal health data is shared on an open channel that makes the IoMT system an easy target for attackers. Therefore, confidentiality and authentication are the key security requirements for an IoMT system. Although few works have been proposed to provide secure communication in conventional healthcare infrastructures, limited work has been done to achieve data confidentiality and authentication in blockchain-based IoMT under fog environment. Therefore, this work proposes a blockchain-assisted certificateless aggregate signcryption called BCSoM scheme that achieves data confidentiality and device/patient authentication. In the proposed work, first, IoMT devices generate a signcrypted text and transmit it to an aggregator that generates an aggregated signcrypted text and sends it to a receiver fog server. The receiver fog server verifies the signcrypted text through the blockchain and also performs unsigncryption to retrieve the original message. The proposed scheme is proven secure under the Discrete Logarithm (DL) and Computational Diffe–Hellman (CDH) assumptions. Finally, a thorough performance analysis using the Hyperledger Fabric platform and cryptographic libraries shows that the proposed scheme is computationally more efficient when compared to existing works.
An increasing number of Internet of Things (IoT) applications are based on a federated environment.Examples include the creation of federations of NATO countries and non-NATO entities participating in missions (Federated Mission Networking) or the interaction of civilian services and the military when providing Humanitarian Assistance And Disaster Relief.Federations are often formed on an ad hoc basis, with the primary goal of combining forces in a federated mission environment at any time, on short notice, and with optimization of the resources involved.One of the leading security challenges in a federated environment of separate IoT administrative domains is effective identity and access management, which is the basis for establishing a relationship of trust and secure communication between IoT devices belonging to different partners.When carrying out missions involving the military and ensuring security, meeting requirements for immediate interoperability is important.In the paper, an attempt has been made to develop a system architecture framework for secure and reliable data streams distribution in a multi-organizational federation environment, where data authentication is based on IoT device identity (fingerprint).Moreover, a hardware-software IoT gateway has been proposed for the verification process and the integration of Hyperledger Fabric's distributed ledger technology, the Apache Kafka message broker, and data-processing microservices implemented using the Kafka Streams API library.The performance tests conducted confirm the suitability of the developed system framework for processing and distributing audiovideo data in a federation IoT environment.Also, a high-level security and reliability assessment was conducted in the paper.
The modern world's increasing reliance on automated systems for everyday tasks has resulted in a corresponding rise in power consumption. The demand is further augmented by increased sales of electric vehicles, smart cities, smart transportation, etc. This growing dependence underscores the critical necessity for a robust smart energy measurement and management system to ensure a continuous and efficient power supply. However, implementing such a system presents a set of challenges, particularly concerning the transparency, security, and trustworthiness of data storage and retrieval. Blockchain technology offers an innovative solution in the form of a distributed ledger, which guarantees secure and transparent transaction storage and retrieval. This research introduces a blockchain-based system, utilising Hyperledger Fabric and smart contracts, designed for the secure storage and retrieval of consumers' energy consumption data. Finally, a user-friendly web portal was designed and developed using the node.js framework, offering an accessible and intuitive interface to monitor and manage energy consumption effectively.
In spite of multiple advantages of the adoption of blockchain (BC), it still faces some integration challenges in modern applications, such as the Internet of Things. These challenges include low throughput rates in permissionless settings. To solve this challenge, several state-of-the-art works proposed sharding (i.e., partitioning) the BC infrastructure. Sharding the network into smaller shards improves the total system throughput, regardless of the node-shard assignment criteria. Most previous work applied a Random Sharding (RS) approach, i.e., randomly allocating nodes into predefined shards, to satisfy the required unpredictability property of node-shard allocation. In this paper, we propose a Blockchain Optimized and Secure Sharding (BOSS) protocol that aims to optimize the node-shard allocation resulting in increased throughput using a variant of the evolutionary Genetic Algorithm. The RS-equivalent levels of security and unpredictability are guaranteed by deploying a distributed random tuning mechanism for the intra-shard weight. We designed BOSS as an extension of the well-defined RS-based RapidChain protocol. We show that the proposed methods can be adapted to other sharding protocols that originally used RS techniques. We implemented and tested our protocol with more than 362,880 cases that covered seven configurable system and optimization parameters. Our evaluation revealed ≈17% average enhancement in scalability, along with a negligible <0.5% mean absolute difference in security levels. To the best of our knowledge, this is the first work that optimizes inter- and intra-shard scalability, with publicly verifiable solutions in permissionless BCs, while maintaining RS-equivalent security and unpredictability.
In the era of digital healthcare, biomedical data sharing is of paramount importance for the advancement of research and personalised healthcare. However, sharing such data while preserving user privacy and ensuring data security poses significant challenges. This paper introduces BioChainReward (BCR), a blockchain-based framework designed to address these concerns. BCR offers enhanced security, privacy, and incentivisation for data sharing in biomedical applications. Its architecture consists of four distinct layers: data, blockchain, smart contract, and application. The data layer handles the encryption and decryption of data, while the blockchain layer manages data hashing and retrieval. The smart contract layer includes an AI-enabled privacy-preservation sublayer that dynamically selects an appropriate privacy technique, tailored to the nature and purpose of each data request. This layer also features a feedback and incentive mechanism that incentivises patients to share their data by offering rewards. Lastly, the application layer serves as an interface for diverse applications, such as AI-enabled apps and data analysis tools, to access and utilise the shared data. Hence, BCR presents a robust, comprehensive approach to secure, privacy-aware, and incentivised data sharing in the biomedical domain.
Ahmad J. Alkhodair, Saraju P. Mohanty, Elias Kougianos
The most essential component of every Distributed Ledger Technology (DLT) is the Consensus Algorithm (CA), which enables users to reach a consensus in a decentralized and distributed manner. Numerous CA exist, but their viability for particular applications varies, making their trade-offs a crucial factor to consider when implementing DLT in a specific field. This article provided a comprehensive analysis of the various consensus algorithms used in distributed ledger technologies (DLT) and blockchain networks. We cover an extensive array of thirty consensus algorithms. Eleven attributes including hardware requirements, pre-trust level, tolerance level, and more, were used to generate a series of comparison tables evaluating these consensus algorithms. In addition, we discuss DLT classifications, the categories of certain consensus algorithms, and provide examples of authentication-focused and data-storage-focused DLTs. In addition, we analyze the pros and cons of particular consensus algorithms, such as Nominated Proof of Stake (NPoS), Bonded Proof of Stake (BPoS), and Avalanche. In conclusion, we discuss the applicability of these consensus algorithms to various Cyber Physical System (CPS) use cases, including supply chain management, intelligent transportation systems, and smart healthcare.
Fog computing composes of neighboring devices, which are connected as cluster to collect and compute data via given algorithms. Compared with cloud computing, it collects and processes data at the edge of device layer, instead of remote data transmission and task scheduling. Fog computing reduces the communication and computation overhead in networking and data aggregating, while preserves data privacy against the cloud center. However, due to the different devices capacities, trust relations, security settings, the concerns are that, if the given data is real and sufficient for analyzing program as input, whether the data processing is done as appointed, and how to prevent secret leakage during the computation. This paper proposes a trustless layer for secure data computing in fog network, where the function accepts “hidden” data as input and generates zero-knowledge computing proof which can be easily verified by public. The combination of secure computing functions and blockchain systems escort trustful business in fog environment.
Blockchain technology promises to be hugely trending and empowering in education domain computing applications. The digital is becoming an integral part of modern life. So as the use of the digital world increases there are more chances of decrease is the security level. So more the use of digitization more the frauds and less the security. In some cases of personal data, leakage has brought back into the focus the security issues with the different identity sharing mechanisms. A customer is expected to provide his identity for authentication by different agencies. So the document verification process deals with the identification of the user. And in turn, provides the required security. The document verification procedures which are used by the colleges are completely dependent on the encryption. This system can be efficient by using Blockchain technology, which has the potential to automate a lot of manual processes and it is also resistant to hacks of any sort. The immutable blockchain block and its distributed ledger is the perfect complement to the process of document verification. With the addition of smart contacts, fraud detection can be automated..
Kithmini Godewatte Arachchige, Philip Branch, Jason But
With the development of Internet of Things (IoT) technologies, industries such as healthcare have started using low-powered sensor-based devices. Because IoT devices are typically low-powered, they are susceptible to cyber intrusions. As an emerging information security solution, blockchain technology has considerable potential for protecting low-powered IoT end devices. Blockchain technology provides promising security features such as cryptography, hash functions, time stamps, and a distributed ledger function. Therefore, blockchain technology can be a robust security technology for securing IoT low-powered devices. However, the integration of blockchain and IoT technologies raises a number of research questions. Scalability is one of the most significant. Blockchain’ scalability of low-powered sensor networks needs to be evaluated to identify the practical application of both technologies in low-powered sensor networks. In this paper, we analyse the scalability limitations of three commonly used blockchain algorithms running on low-powered single-board computers communicating in a wireless sensor network. We assess the scalability limitations of three blockchain networks as we increase the number of nodes. Our analysis shows considerable scalability variations between three blockchain networks. The results indicate that some blockchain networks can have over 800 ms network latency and some blockchain networks may use a bandwidth over 1600 Kbps. This work will contribute to developing efficient blockchain-based IoT sensor networks.
Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system diversity, bandwidth diversity, node diversity, etc., for decision-making of data transactions across blockchain-based heterogeneous networks. Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems. To address these issues, today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain. The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network. This paper proposes a full-fledged taxonomy to identify the main obstacles, research gaps, future research directions, effective solutions, and most relevant blockchain-enabled cybersecurity systems. In addition, Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper to meet the goal of maintaining optimal performance data transactions among organizations. Overall, this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network.
Malka N. Halgamuge, Geetha. K. Munasinghe, Moshe Zukerman
The Internet of Things (IoT) has emerged with Distributed Ledger Technology (DLT) to address existing scalability challenges and improve the trustworthiness of machine-to-machine communication. Among the numerous potential benefits of combining IoT and DLT, Blockchain, a subset of DLT, is a crucial enabler to accelerate secure IoT adoption. Appending a new block to a blockchain, especially in a blockchain-based IoT ecosystem, requires more delay than expected. This delay is one of several issues limiting the broader adoption of blockchain within the IoT domain. To assess this delay, we develop a new comprehensive model to estimate the time required to generate a new block in a blockchain-enabled IoT system. To this end, we develop sub-computation models and compare time consumption associated with the block generation process by conducting an extensive analysis of the following selected IoT layers: device layer, cluster head layer, fog/edge layer, and cloud layer. Our study identifies potential time-consuming steps in adding a new block to a network. Our results demonstrate that the type of blockchain framework and data encryption algorithms could affect the block generation time and that Avalanche, Conflux, Algorand, Polkadot Hyperledger Fabric outperforms Ethereum in terms of block generation time in IoT networks. On the other hand, the blockchain framework does not play a significant role in block generation time for smaller data packets. We also observed the benefit of using 256-bit ECC (elliptic curve cryptography) encryption and the fog layer in IoT networks to enhance the scalability of the block generation process. All in all, our results indicate that the total block generation time varies depending on the selected IoT framework, data encryption algorithm, blockchain type, and key functions of the layers. However, we found that time delays associated with queuing or block size are negligible relative to the other key components of block generation time.
Yuvraj Singh, M. A. Jabbar, Shishir Kumar Shandilya, Олена Вовк · 5 authors
Blockchain technology includes numerous elements such as distributed ledgers, decentralization, authenticity, privacy, and immutability. It has progressed past the hype to find actual use cases in industries like healthcare. Blockchain is an emerging area that relies on a consensus algorithm and the idea of a digitally distributed ledger to eliminate any intermediary risks. By enabling them to trace data provenance and any changes made, blockchain technology can enable different healthcare stakeholders to share access to their networks without violating data security and integrity. The healthcare industry faces challenges like fragmented data, security and privacy concerns, and interoperability issues. Blockchain technology offers potential solutions by ensuring secure, tamper-proof storage across multiple network nodes, improving interoperability and patient privacy. Encrypting patient data further enhances security and reduces unauthorized access concerns. Blockchain technology, deployed over the Internet, can potentially use the current healthcare data by using a patient-centric approach and removing the intermediaries. This paper discusses the effective utilization of blockchain technology in the healthcare industry. In contrast to other applications, the exoteric evaluation in this paper shows that the innovative technology called blockchain technology has a major role to play in the existing and future applications of the healthcare industry and has significant benefits.
Nur Khairunnisa Noorhizama, Zubaile Abdullah, Shahreen Kasim, Isredza Rahmi A. Hamid · 5 authors
One of the major challenges the university faces is to provide real-time verification of their student's degree certification upon request by other parties. Conventional verification systems are typically costly, time-consuming and bureaucratic against certificate credential misconduct. In addition, the forgery of graduation degree certificates has become more efficient due to easy-to-use scanning, editing, and printing technologies. Therefore, this research proposes verifying Ph.D. certificates using QR codes on the Ethereum blockchain to address certificate verification challenges. Blockchain technology ensures tamper-proof and decentralized management of degree certificates as the certificates stored on the blockchain are replicated across the network. The issuance of certificates requires the use of the issuer's private key, thus preventing forgery. The system was developed using Solidity for the smart contract, PHP, HTML/CSS for the web-based implementation, and MetaMask for blockchain integration. User testing confirmed the successful implementation and functionality of the system. Users can add, update, and delete certificates, generate and scan QR codes, and receive instant verification feedback. The verification system effectively meets all requirements, providing a robust solution for validating Ph.D. certificates. Future research may focus on scalability and adoption, privacy and data protection, user experience, and integration with existing systems. Other researchers can optimize the verification system for widespread adoption and utilization by exploring these areas. This research contributes to securing and efficiently verifying academic certificates using QR codes on the Ethereum blockchain. Ultimately, this work advances the field of certificate verification and promotes trust in academic credentials.
Kiran Bala, Ramakant Upadhyay, Syed Rashid Anwar, G. Shrimal
Intelligent Transportation System (ITS) heavily relies on the unique mobile ad-hoc network (MANET) known as the vehicular ad-hoc network (VANET). The convenience that the Location Based Service (LBS), security issues arising from VANETs' great portability. Among the most widely used privacy-preserving techniques, distributed k-anonymity does not consider users' reliability, which results in hostile vehicle tracking. Therefore, Blockchain-enabled, Trust and Location dependent-Privacy Preserving (BTLB-PP) authentication system in VANET to overcome issues. Trust Management (TM) based on Dirichlet distribution, client and member will only collaborate with vehicles they confide by explicitly examining various prerequisites of claimed vehicle and collaborative vehicle during construction of unidentified obfuscation region and integrating attributes of these two functions. Using blockchain, a data structure has been proposed to promptly register trust of vehicles on publicly available blocks, allowing any vehicle to retrieve. In the trials, tests on various datasets have been run. Suggested system is resistant to multiple trust model threats, improving the security of vehicles' confidentiality and privacy. The performance evaluation metrics are precision, recall, f-measure and false positive rate (FPR) are used to evaluate the proposed system. Results from the simulation show that the proposed method is efficient and practical in reality. The suggested method was tested in a simulated traffic situation to verify its effectiveness.
Micro-credentials can provide easily accessible and transparent evidence of skills or knowledge that have been certified by an authority, based on small units of learning. The recognition and transfer of credits is becoming essential, as an increasing number of students are studying at different institutions, often at the same time, online or in traditional settings. "Blockchain is a type of database that stores data in an "open, peer-to-peer (P2P) network that favors communal functionality in lieu of a centralized controlling entity" (Columbia Engineering Bootcamps, 2021, para 5). The development of blockchain (https://theconversation.com/demystifying-the-blockchain-a-basic-user-guide-60226) holds promise of becoming a useful facilitator for supporting the storage and dissemination of micro-credentials on a global scale. Besides providing effective data security and privacy, blockchain can also facilitate maintaining and disseminating credentials, while ensuring that access is readily available for students under their control. Because of its immutability, blockchain can be used to confidently attest to students' accomplishments and is therefore particularly appropriate for micro-credentials.
Ye Cheng, Yihao Guo, Minghui Xu, Qin Hu · 6 authors
A metaverse breaks the boundaries of time and space between people, realizing a more realistic virtual experience, improving work efficiency, and creating a new business model. Blockchain, as one of the key supporting technologies for a metaverse design, provides a trusted interactive environment. However, the rich and varied scenes of a metaverse have led to excessive consumption of on-chain resources, raising the threshold for ordinary users to join, thereby losing the human-centered design. Therefore, we propose an adaptive and modular blockchain-enabled architecture for a decentralized metaverse to address these issues. The solution includes an adaptive consensus/ledger protocol based on a modular blockchain, which can effectively adapt to the ever-changing scenarios of the metaverse, reduce resource consumption, and provide a secure and reliable interactive environment. In addition, we propose the concept of Non-Fungible Resource (NFR) to virtualize idle resources. Users can establish a temporary trusted environment and rent others' NFR to meet their computing needs. Finally, we simulate and test our solution based on XuperChain, and the experimental results prove the feasibility of our design.
Arvind Kumar Pandey, Rini Saxena, Aishwary Awasthi, M P Sunil
The Industrial Internet of Things (IIoT) paradigm's fast expansion in the amount of information created from linked devices creates new opportunities for improving the service quality and applications through sharing of data. Data security is a significant problem since training and Support Vector Machine (SVM) classifier often involves compiling tagged IoT data from several organizations. Beyond causing the suppliers to lose money, disclosing sensitive information might cause significant problems. To solve these issues, introduced a secure SVM, which is a Privacy-Preserving SVM (PP-SVM) training method using block chain-based encoded IoT data, to fill the void between ideal assumptions and practical restrictions. IoT messages are encrypted before being stored on a decentralized system because Block chain offers safe and dependable data exchange platforms across several data sources. Using a homomorphic cryptographic algorithm, Paillier, reliable modules have been developed, such as protected algebraic multiplying and protected comparison. Furthermore, a protected SVM learning algorithm that only needs two conversations during a single step has been created. According to stringent security assessment, proposed approach guarantees SVM model parameters for data professionals and secrecy of sensitive information for each data source. Extensive testing backs up effectiveness of the suggested plan.
The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.
Low Power and Lossy Networks (LLNs) are a class of networks characterized by constrained resources, intermittent connectivity, and potential lossy links. These networks find applications in various domains such as Internet of Things (IoT), smart grids, and industrial automation. However, the inherent challenges of LLNs, including energy efficiency, routing reliability, and scalability, have prompted researchers to explore innovative solutions. Blockchain, a de -centralized and secure distributed ledger technology, has emerged as a potential candidate to address these challenges. This systematic review aims to comprehensively analyze and evaluate the existing research on utilizing blockchain solutions for routing protocols in LLNs. The review follows a structured methodology to identify, categorize, and critically assess the state -of -the -art research contributions in this domain.