Maha Kadadha, Shakti Singh, Rabeb Mizouni, Hadi Otrok
Crowdsourcing is a rapidly growing paradigm that commercial platforms such as Amazon MTurk and UpWork are adopting for allocating tasks to workers. Such frameworks typically employ a centralized infrastructure to implement required mechanisms such as task allocation, submission evaluation, and payment computation. However, centralized deployment comes with unresolved challenges in terms of trust, reliability, and transparency. Blockchain technology has been embraced for the deployment of crowdsourcing frameworks to enable trusted and autonomous execution. Each of the existing Blockchain-based crowdsourcing/ crowdsensing framework targets a specific application context due to the constraint capabilities of Blockchain. In this paper, we propose a context-aware Blockchain-based crowdsourcing framework where the context is defined by task requirements and workers’ availability. The proposed framework is developed upon the review of existing works integrating Blockchain and crowdsourcing where the challenges and future directions are identified. The proposed framework has two classes of components: 1)core componentsimplementing the basic framework functionalities, and 2)advanced componentswhich are context and data managers that help improve the framework performance. TheAdvanced Context Manageris designed to monitor the current context and select the mechanisms to run for the core components accordingly. The core components are implemented as smart contracts on Blockchain for autonomous and trusted execution, while the advanced components are implemented spanning Blockchain and the cloud for flexibility and scalability. A case study demonstrating the performance of context-aware task allocation algorithms is presented. It shows how capturing the current system context can help achieve better overall performance based on the objective of the sensing application under consideration.
Blockchain technology is regarded as the emergent security solution for many applications related to the Internet of Things (<i>IoT</i>). In concept, blockchain has a linear structure that grows with the number of transactions entered. This growth in size is the main obstacle to the blockchain, which makes it unsuitable for resource-constrained IoT environments. Moreover, conventional consensus algorithms such as PoW, PoS are very computationally heavy. This paper solves these problems by introducing a new lightweight blockchain structure and lightweight consensus algorithm. The Multi-Zone Direct Acyclic Graph (DAG) Blockchain (<i>Multizone-DAG-Blockchain</i>) framework is proposed for the fog-based IoT environment. In this context, fog computing technology is integrated with the IoT to offload IoT tasks to the fog nodes, thus preserving the energy consumption of the IoT devices. Both IoT and fog nodes are initially authenticated using a non-cloneable physical function- based validation mechanism (<i>DPUF-VM</i>) in which multiple authentication certificates are verified in the blockchain. Each transaction is stored in a hash function in the blockchain using the lightweight CubeHash algorithm and signed by the Four-Q- Curve algorithm. In the cloud, sensitive data is stored as ciphertext. Fog nodes provide data security to avoid the energy consumption and complexity of IoT nodes. The fog node first performs a redundancy analysis using the Jaccard Similarity (JS) measure and sensitivity analysis using the Neutrosophic Neural Intelligent Network (<i>N2IN</i>) algorithm. A lightweight proof-of-authentication (<i>PoAh</i>) algorithm is presented and executed by the optimal consensus node selected by the bi- objective spiral optimization (<i>BoSo</i>) algorithm for transaction validation. The proposed work is modeled in Network Simulator 3.26 (ns-3.26), and the performance is evaluated in terms of energy consumption, storage cost, response time, and throughput.
With the development of Internet of things (IoT) technology, a large-scale, heterogeneous and dynamic distributed IoT environment has gradually formed between different IoTs. In order to solve the scalability problem of restricted device access management in the Internet of things, a distributed access control system model of the Internet of things based on blockchain technology is proposed. The system model adopts a single smart contract, which simplifies the whole process in the blockchain network and reduces the communication overhead between nodes. According to the simulation results and evaluation, it is proved that the solution has good scalability.
With the substantial increase in the number of smart cars, vehicular ad hoc network (VANET), where data can be shared between vehicles to enrich existing vehicle services and improve driving safety, is gaining more and more attention, thus creating a more efficient intelligent transportation system. Moreover, the in‐depth research and development of 6G and AI technology further strengthen the interconnection of various entities in VANET and can realize edge intelligence, which fundamentally enhances the efficiency of data sharing. However, reliable transmission and secure storage of data have always been a great challenge in data sharing. Although some schemes store shared data in the blockchain, most of the consensus mechanisms they use employ full nodes to verify signature information and timestamps, which cannot effectively judge the reliability of the shared data itself. Some other schemes use scoring mechanisms to evaluate data uploaded by vehicles, but these methods can be affected by network hardware failures and cannot effectively detect duplicate data. In addition, participants’ privacy may also be disclosed in the process of data sharing, such as participants’ location and identity information. Therefore, to address the above problems, this paper proposes a data sharing scheme in 6G‐VANET, which can not only ensure the reliability and security of shared data but also protect the privacy of participants. Firstly, a consortium chain is adopted to realize the secure storage of shared data in 6G‐VANET, which meets the requirements of tamper‐proof and traceability of data. Secondly, a voting consensus mechanism is designed in combination with smart contract to ensure the reliability of data. Thirdly, the trained word2vec natural language processing model is deployed to edge nodes to realize edge intelligence, effectively eliminate the duplicate shared data, and enhance storage efficiency. Finally, a participant privacy protection mechanism is designed using the Private Set Intersection (PSI) protocol, and a secure and efficient data sharing scheme is finally realized. The effectiveness of the proposed scheme is demonstrated by security analysis and experimental evaluation. The experimental results show that the time and space overhead of blockchain can meet the practical requirements, and the proposed PSI protocol of large‐scale vehicles can be completed in a short time.
This paper shows the performance and scalability evaluation of different blockchain platform implementations. Hyperledger Iroha implementing YAC consensus, Sawtooth implementing PoET algorithm, and Hyperledger Fabric framework implementation. Performance evaluation and scalability assessment were done by varying different sets of parameters such as block size, transaction sending rate, network traffic distribution, and network size. Performance evaluation was done based on average transaction latency, network throughput, and transaction failure rate. Scalability was assessed based on changes in transaction latency and throughput with increasing network size. Test results let to study the impact of a particular parameter on the private blockchain network performance and show how they can be adjusted to improve performance.
Nowadays, due to the evolution of information technologies and their adoption in the healthcare domain, new risks to medical data protection and patient privacy are increasingly present. It is therefore important to implement approaches that can prevent rapidly emerging cyber-attacks. Essentially, the adoption of cyber security measures in healthcare should be oriented towards a better assurance of patient rights and consent management. Blockchain is one of the most advanced technologies that can deal with many types of cyber threats ensuring the integrity, availability, and privacy of the data. It adds elements of trust and traceability to the data exchange processes deployed within Hospital information systems and beyond. In this paper, we study the usability of blockchain in the healthcare domain and we develop a data exchange approach based on the Hyperledger Blockchain model. The focus here will be mainly on privacy concerns and the integration of patient consent in the data sharing operational controls.
With the rapid development of the IoT (Internet-of-Things), additional smart gadgets may be associated with the Internet, significantly enhancing data transfer and communication. Software-Defined Networking (SDN) is known as a new model that separates the control plane and the data plane, and is anticipated as a favorable solution for implementing Blockchain, to offer the scalability and adaptability required for IoT. The scalability of the network rises in direct proportion to the users’ enhanced privacy on the network. Blockchain and SDN are two top innovations utilized to create secure network architectures and provide trustworthy data transmission. They offer a strong and trustworthy platform to deal with dangers and problems, including security, privacy, adaptability, scalability, and secrecy. Unfortunately, the attackers can still inject traffic to disrupt a blockchain node’s regular functions. This study provides an optimized Blockchain-based SD IoT architecture for smart networks that is safe and energy-efficient. In this work, it is concentrated on blockchain-based SDN and creates an SDN-Blockchain Classifier. This IDS-based security tool provides a trust-based classifier by handling and reducing harmful traffic through traffic fusion and aggregation. Finally, it is concluded by evaluating the proposed framework SDN-Blockchain Classifier performance against MAC flooding attack in a simulation setting and demonstrating that it can attain optimized average throughput, response time, packet loss of crossing domain path, energy efficiency, end-to-end delay, file transfer operation, energy consumption, and CPU utilization compared to the baselines taken into consideration, thereby achieving efficacy and also security in the proposed smart network.
Abstract The core objective of the concept of International Data Spaces (IDS) is to enable controlled exchange and sharing of data between organizations, regardless of the type of data. Sharing of data will generate services that become an asset while data providers maintain their sovereignty. IDS furnish a technology enabler for implementing data economies to exchange data and knowledge, which are according to usage policies. Thus, data turns into an economic asset. However, once data have been provided toward IDS, sovereignty of data owners is of pivotal importance, as well as the question of its use and the transfer of incentives to providers. At this point, blockchain technology enters the ballpark. It is instrumental for the implementation and operation of clearing houses as trading platform for data provision and knowledge utilization. The aim of this chapter is to examine and discuss the role of blockchain for IDS. Next to general blockchain foundations and potentials, blockchain’s specific potential for IDS is discussed and its application is demonstrated by four compelling use cases.
The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features. This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for Ethereum and be able to solve interesting blockchain problems associated with virtual machines and smart contracts. Using my virtual machine implementation, I was able to produce a simplified token that resembles Ethereum tokens and works with SpartanGold. This token demonstrates the SpartanGold Virtual Machine’s usefulness in simulating smart contracts of real world interest. Going forward, developers can experiment with the SpartanGold Virtual Machine to test out new ideas without dealing with the full complexity of the Ethereum Virtual Machine.
In this paper, a blockchain‐based secure routing model is proposed for the Internet of Sensor Things (IoST). The blockchain is used to register the nodes and store the data packets’ transactions. Moreover, the Proof of Authority (PoA) consensus mechanism is used in the model to avoid the extra overhead incurred due to the use of Proof of Work (PoW) consensus mechanism. Furthermore, during routing of data packets, malicious nodes can exist in the IoST network, which eavesdrop the communication. Therefore, the Genetic Algorithm‐based Support Vector Machine (GA‐SVM) and Genetic Algorithm‐based Decision Tree (GA‐DT) models are proposed for malicious node detection. After the malicious node detection, the Dijkstra algorithm is used to find the optimal routing path in the network. The simulation results show the effectiveness of the proposed model. PoA is compared with PoW in terms of the transaction cost in which PoA has consumed 30% less cost than PoW. Furthermore, without Man In The Middle (MITM) attack, GA‐SVM consumes 10% less energy than with MITM attack. Moreover, without any attack, GA‐SVM consumes 30% less than grayhole attack and 60% less energy than mistreatment. The results of Decision Tree (DT), Support Vector Machine (SVM), GA‐DT, and GA‐SVM are compared in terms of accuracy and precision. The accuracy of DT, SVM, GA‐DT, and GA‐SVM is 88%, 93%, 96%, and 98%, respectively. The precision of DT, SVM, GA‐DT, and GA‐SVM is 100%, 92%, 94%, and 96%, respectively. In addition, the Dijkstra algorithm is compared with Bellman Ford algorithm. The shortest distances calculated by Dijkstra and Bellman are 8 and 11 hops long, respectively. Also, security analysis is performed to check the smart contract’s effectiveness against attacks. Moreover, we induced three attacks: grayhole attack, mistreatment attack, and MITM attack to check the resilience of our proposed system model.
Yangqun Li, Jin Qi, Lijuan Min, Hongzhi Yang · 6 authors
Web of Things (WoT) resources are not only numerous, but also have a wide range of applications and deployments. The centralized WoT resource sharing mechanism lacks flexibility and scalability, and hence cannot satisfy requirement of distributed resource sharing in large-scale environment. In response to this problem, a trusted and secure mechanism for WoT resources sharing based on context and blockchain (CWoT-Share) was proposed. Firstly, the mechanism can respond quickly to the changes of the application environment by dynamically determining resource access control rules according to the context. Then, the flexible resource charging strategies, which reduced the fees paid by the users who shared more resources and increased the fees paid by users who frequently used resources maliciously, were used to fulfill efficient sharing of WoT resources. Meanwhile, the charging strategies also achieve load balancing by dynamic selection of WoT resources. Finally, the open source blockchain platform Ethereum was used for the simulation and the simulation results show that CWoT-Share can flexibly adapt to the application environment and dynamically adjust strategies of resource access control and resource charging.
D. N. Rao, G. Vidhya, M. Rajesh, Vipin Jain · 7 authors
The new IoT apps will not be able to inspire people to utilize them and may ultimately lose all their potential if an interoperable and trustworthy ecosystem is not provided. IoT has its extra security difficulties such as information storage, administration, privacy concerns, and authentication. The presently deployed IoT apps have encountered various security and privacy assaults globally. Due to being less secure and low powered, the IoT devices present a simple entryway to the adversaries to obtain access to the corporate networks, leading to giving easy control over all of the data of the users. The objective of this doctorate proposed work will be to solve the security associated difficulties in multiple IoT domains like the e‐commerce, vehicular ad hoc networks (VANET), mobile ad hoc networks (MANET), and Internet of Drones (IoD). The proposed study focuses on the development of a distributed framework for IoT based on blockchain. The framework includes the usage of Ethereum‐based smart contracts and auction models to increase the income and QoS for both the seller and the buyer and the development of a DAG chain‐based distributed framework for parking lot allocation in a network of automobiles. The suggested model includes the requirement of obtaining agreement among the nodes with probability one in such a circumstance. The suggested model demonstrates to be predictable as typical voting‐based consensus protocols like Practical Byzantine Fault Tolerance (PBFT) and at the same time can accommodate a high number of nodes even in an asynchronous setting. Research on Byzantine fault‐tolerant systems has been ongoing for more than four decades, and although the solutions were shown to be feasible early on, they remained unworkable for a long time. With PBFT, the first feasible solution was provided in 1999, and this sparked fresh research that has resulted in unique applications that are still being developed today employing this technology. Despite the fact that the safety and liveness properties of PBFT‐type protocols have been thoroughly investigated, when it comes to practical performance, only empirical results—often obtained in artificial environments—are known, and imperfections in the communication channels are not explicitly considered. It is our goal in this paper to propose the first performance model for PBFT that takes into account the effect of unreliable channels as well as the usage of alternative transport protocols across those channels. We also performed a large number of simulations to test the model and acquire a better understanding of the influence of different deployment factors on the total transaction timeframe.
The development of online education has broken the limitations of traditional education in region and time, and promoted the reform of education. However, there are some problems in traditional online education, such as data island, lack of data sharing model and so on. This paper constructs an online education data management model based on blockchain technology, which solves the problems of trust authentication of online learning data and curriculum resources; We put forward the trust generation and security sharing mechanism of online education data, analyze its security, and realize the security sharing of online education data on the basis of privacy protection.
Nwosu Anthony Ugochukwu, S. B. Goyal, A. Sampathkumar
As the global logistics business expands as a result of the industrial 4.0 revolution, logistics operations continue to evolve as new technologies such as IoT, cloud, and big data are deployed. These IoT devices improve the logistics function by boosting real‐time product tracking, improved data collection, smart storage of logistics data, etc. Some of these new technologies present an avenue for cyberattacks on these logistics systems due to their centralized database structure. Logistics operations entail the exchange of private consumer information (name, address, phone number, and bank account information) as well as product information amongst logistics stakeholders (manufacturers, suppliers, transporters, and customers). And the engagement of so many logistics stakeholders creates privacy and security issues for the private information because customer information, as well as product details, are transferred and shared across different logistical stakeholders during the logistics process. It faces unwanted access, which could lead to fraud or the creation of counterfeit products by a bad actor in the system. All of these challenges are significant because logistics data integrity is important for customer satisfaction. The deployment of Blockchain innovation will address these challenges with the application of its special feature such as immutability, efficient cryptography, and distributed decentralized storage system. In this paper, we highlighted the technology that enables smart logistics and reviewed smart logistics, Blockchain, and IoT in logistics; we present the significance of integrating Blockchain and IoT in logistics. We proposed a Blockchain‐based IoT‐enabled system framework for secure and efficient logistics management where logistics data can be captured with the use of IoT sensors, and we also designed and describe the sequence diagram for secured communication between the logistics stakeholder through a smart contract. In conclusion, Blockchain can provide security to logistics data and enhance operational efficiency with its key features.
Tariq Al-Abri, Ahmet Önen, Rashid Al Abri, Abdulnasir Hossen · 7 authors
With the rapid transformation of the energy sector towards modern power systems represented by smart grids (SGs), microgrids (MG), and distributed generation, blockchain (BC) technology has shown the capability for solving security, privacy, and reliability challenges that hinder progress. Currently, the energy structure is forming a decentralized system that prioritizes customer satisfaction. BC technology undertakes power network stockholders in a secure energy market, transparent transactions, and fair competition and offers promising energy solutions. This paper is a comprehensive review of energy applications using BC integration. Firstly, we introduce the drivers of BC leverage that make it a potentially important component of the power network. Following that, we provide background information on BC and its application in areas other than the energy sector. Subsequently, we discuss studies and sort potential energy applications from various recent papers and surveys that have already adopted BC technology in the energy sector. Then, we summarize the pricing infrastructure for applying BC in the energy sector and identify the requirements to build it. Finally, energy security and privacy challenges based on BC are highlighted, along with potential drawbacks and concerns related to the pricing infrastructure.
AI collaboration increasingly spans untrusted, heterogeneous nodes from edge devices to multi-clouds raising acute concerns around privacy, integrity, and verifiability of shared models and updates. This paper proposes a secure distributed computing framework that unifies privacy-preserving learning, verifiable coordination, and incentive-aligned governance for decentralized AI model sharing. The architecture composes federated and peer-to-peer training with secure aggregation, differential privacy, and hardware-backed confidential computing to prevent data leakage while mitigating gradient inversion risks. Model provenance, access control, and policy enforcement are anchored via a lightweight, append-only ledger with decentralized identifiers, enabling auditability without central authorities. To counter poisoning, backdoors, and Sybil attacks, the framework integrates robust aggregation, reputation-weighted participation, and update attestation with zero-knowledge proofs for selective disclosure. A resource-aware scheduler adapts to edge variability using gossip-based dissemination, opportunistic bandwidth utilization, and erasure-coded checkpoints to preserve liveness under churn. Interoperability is ensured through portable model artifacts (e.g., ONNX), secure enclaves for cross-framework execution, and privacy budgets tracked as first-class governance assets. We outline threat models, compliance hooks for jurisdictional constraints, and a token-free contribution accounting mechanism that rewards data quality and validation work. Simulated and real-world deployments illustrate improved end-to-end trust, reduced coordination overhead, and resilient performance under adversarial conditions, positioning the framework as a practical substrate for open, secure, and accountable AI collaboration in decentralized environments
Muhammad Shoaib Farooq, Mishaal Ahmed, Muhammad Emran
Requirements are the basis of software development practices. Ambiguities in requirements lead a project to a point of failure or penalize it with a high budget and time for defect traceability. The ever-growing demand for advanced computing systems has increased the complexity of Software Requirements Engineering (SRE) practices. Blockchain systems require specialized SRE practices as the issues of Requirement Traceability (RT), developer/client confidentiality, and Requirement Negotiation (RN) typically exist in conventional approaches, which require more improvement. Moreover, blockchain technology incorporates the capacity to function as an infrastructure for the SRE framework providing transparency, security, and reliability. Even though the significance of studying blockchain in the context of SRE is evident, it is still in its infancy. None of the previous studies surveyed this domain to the best of our knowledge. We aim to summarize the scholarly contributions of blockchain acquainted SRE from 2015 to 2021 and to provide academia and practitioners with in-depth knowledge about this domain. In this article, we have provided a novel comprehensive review of the aspects of blockchain-acquainted SRE practices. We have presented SRE-based quality improvement factors and outlined the need for blockchain technology in this domain. Furthermore, we have classified SRE practices based on blockchain engineering. In addition, we have proposed a generic SRE model built on blockchain infrastructure along with its workflows. Similarly, we have provided implementation guidelines for the future development guidance of SRE applications built on blockchain technology. Finally, we have presented the current research challenges and provided future directions based on blockchain acquainted SRE.
Recently, the Healthcare Internet of Things (H-IoT) has been widely applied to alleviate the global challenge of the coronavirus disease 2019 (COVID-19) pandemic. However, security and limited energy capacity issues remain the two main factors that prevent the large-scale application of the H-IoT. Therefore, a permissioned blockchain and deep reinforcement learning (DRL)-empowered H-IoT system is presented in this research to address these two issues. The proposed H-IoT system can provide real-time security and energy-efficient healthcare services to control the propagation of the COVID-19 pandemic. To address the security issue, a permissioned blockchain method is adopted to guarantee the security of the proposed H-IoT system. As for handling the limited energy constraint, we employ the mobile edge computing (MEC) method to offload the computing tasks to alleviate the computational burden and energy consumption of the proposed H-IoT system. We also adopt an energy harvesting method to improve performance. In addition, a DRL method is employed to jointly optimize both the security and energy efficiency performance of the proposed system. The simulation results demonstrate that the proposed solution can balance the requirements of security and energy efficiency issues and hence can better respond to the COVID-19 pandemic.
Blockchain technology was once exclusively associated with cryptocurrencies, but now it has become a powerful force that can reshape industries outside of finance. The concept of decentralized networks is transforming how we manage identity, value, ownership, and even governance. As seen previously, blockchain applications extend into sectors like healthcare, supply chains, social media, finance, and even national infrastructure projects.
Humberto Jorge De Moura Costa, Cristiano André da Costa, Rodrigo da Rosa Righi, Rodolfo Stoffel Antunes · 6 authors
Nowadays, there are many fragmented records of patient’s health data in different locations like hospitals, clinics, and organizations all around the world. With the arrival of the COVID-19 pandemic, several governments and institutions struggled to have satisfactory, fast, and accurate decision-making in a wide, dispersed, and global environment. In the current literature, we found that the most common related challenges include delay (network latency), software scalability, health data privacy, and global patient identification. We propose to design, implement and evaluate a healthcare software architecture focused on a global vaccination strategy, considering healthcare privacy issues, latency mitigation, support of scalability, and the use of a global identification. We have designed and implemented a prototype of a healthcare software called Fog-Care, evaluating performance metrics like latency, throughput and send rate of a hypothetical scenario where a global integrated vaccination campaign is adopted in wide dispensed locations (Brazil, USA, and United Kingdom), with an approach based on blockchain, unique identity, and fog computing technologies. The evaluation results demonstrate that the minimum latency spends less than 1 second to run, and the average of this metric grows in a linear progression, showing that a decentralized infrastructure integrating blockchain, global unique identification, and fog computing are feasible to make a scalable solution for a global vaccination campaign within other hospitals, clinics, and research institutions around the world and its data-sharing issues of privacy, and identification.
IoT (IoT) networks generate massive amounts of data while supporting various applications, where the security and protection of IoT data are very important. In particular, blockchain technology supporting IoT networks is considered as the most secure, expandable, and scalable database storage solution. However, existing blockchain systems have scalability problems due to low throughput and high resource consumption, and security problems due to malicious attacks. Several studies have proposed blockchain technologies that can improve the scalability or the security level, but there have been few studies that improve both at the same time. In addition, most existing studies do not consider malicious attack scenarios in the consensus process, which deteriorates the blockchain security level. In order to solve the scalability and security problems simultaneously, this paper proposes a Dueling Double Deep-Q-network with Prioritized experience replay (D3P) based secure trust-based delegated consensus blockchain (TDCB-D3P) scheme that optimizes the blockchain performance by applying deep reinforcement learning (DRL) technology. The TDCB-D3P scheme uses a trust system with a delegated consensus algorithm to ensure the security level and reduce computing costs. In addition, DRL is used to compute the optimum blockchain parameters under the dynamic network state and maximize the transactions per second (TPS) performance and security level. The simulation results show that the TDCB-D3P scheme can provide a superior TPS and resource consumption performance. Furthermore, in blockchain networks with malicious nodes, the simulation results show that the proposed scheme significantly improves the security level when compared to existing blockchain schemes by effectively reducing the influence of malicious nodes.
In recent years, the spread of information and communication technology has led to the emergence of e-government, which is the electronic replacement of government services. E-government is said to be compatible with blockchain technology, which has led to various studies on the possibility. Notarization, one of the functions of the government, has particularly been examined for the potential adoption of blockchain technology. However, because the notary public must authenticate the document’s contents during the notarization process, they have been difficult to replace with smart contracts. In this study, we focus only on fixed date notarizations and propose a fully automated notarization system by combining a national eID card with Public Key Infrastructure and smart contracts. A fixed date is a notarization that allows a notary public to guarantee that a document existed, regardless of the authenticity of the document’s content. Therefore, it can be replaced by a smart contract. Specifically, our proposed system automatically authenticates the creator and the document for electronic documents signed with a national eID card and uses the transaction receipt generated when the information is stored on the blockchain as a certificate of notarization. Verification of the signed data is done inside the blockchain by smart contracts, which eliminates the need for a verification authority. We further demonstrate the effectiveness of the proposed method in a Japanese use case as proof of concept.
In the development of technology in various fields like big data analysis, data mining, big data, cloud computing, and blockchain technology, security become more constrained. Blockchain is used in providing security by encrypting the sharing of information. Blockchain is applied in the peer-to-peer (P2P) network and it has a decentralized ledger. Providing security against unauthorized breaches in the distributed network is required. To detect unauthorized breaches, there are numerous techniques were developed and those techniques are inefficient and have poor data integrity. Hence, a novel technique needs to be implemented to tackle the new breaches in the distributed network. This paper, proposed a hybrid technique of two fish with a ripple consensus algorithm (TF-RC). To improve the detection time and security, this paper uses efficient transmission of data in the distributed network. The experimental analysis of TF-RC by using the metric measures of performance in terms of latency, throughput, energy efficiency and it produced better performance.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques