We are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish. [1]â[3]. In this new epoch, the collaboration of data and knowledge, humans and machines, actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation, unveiling an open future full of boundless possibilities. However, the value of dispersed data extends far beyond passive storage and application. Instead, it has become an incentive and driving force that connects different workers in different worlds, forming a more powerful network of knowledge. No longer monopolized by a select few organizations or companies, the community-driven data sharing and exchange enable every individual to participate and contribute [4]â[6]. The diversification, sharing and integration of data create numerous avenues for learning, exploration, and innovation.
Sushruta Mishra, Soham Chakraborty, Kshira Sagar Sahoo, Muhammad Bilal
The advent of the Internet of Things (IoT) has resulted in significant technical development in the healthcare sector, enabling the establishment of Medical Cyber-Physical Systems (MCPS). The increased number of MCPS generates a massive amount of privacy-sensitive data, hence it is important to enhance the security of devices and data transmission in MCPS. Earlier several research studies were undertaken in order to enhance security in healthcare, but none of them could adapt to changing behaviors of data attacks. Here the role of blockchain and Reinforcement Learning (RL) comes into play since it can adjust itself to the nature of changing attacks, thus preventing any kind of attacks. This work proposes a solution, named Cogni-Sec, which employs a decentralized cognitive blockchain and Reinforcement Learning architecture and addresses the security issue. Blockchain is incorporated in the approach for data storage and transmission to increase the degree of security in the MCPS modules. Hyperledger Fabric is applied as the blockchain base which shows transaction query results with nearly 10% increased throughput, 69% less memory consumption, and 15% lower CPU usage when compared to Ethereum. Further security risk at the block mining level within a blockchain network is reduced by introducing distributed Reinforcement Learning architecture in replacement for the miner nodes, which imitates the cognitive behavior of miners in a distributed environment. Different multi-agent learning systems have been evaluated for building the mining agent. Among these, the a3c agent in distributed learning setup yields the optimum cumulative reward with a median value of 54.5 and minimizes the maximum number of data threats.
Abstract Distributed ledger technologies (DLTs) are considered one of the foremost emerging technologies which can contribute to transform cities to smarter cities. DLT play important role in municipalities to accelerate the digitalization process toward changing the roles and services of enterprises in sustainable smart cities. Standardization of DLTs aids to reduce data and digital assets silos while decreasing vendor lock-in across distributed applications enabling a digital urban ecosystem that supports migration capabilities making it possible for cities to seamlessly achieve interoperability among DLTs and centralized digital platforms, although a few standards such as IEEE 2418, IEEE P2418.5, and ISO/TC 307 have been developed. The alignment and integration mechanisms required to support standardization of DLT for interoperable services in smart cities is lacking. Therefore, this study presents an understanding on current and open issues on standardization of DLTs in sustainable smart cities with a specific focus on data integration and alignment efforts related to interoperable DLTs. A framework is developed to promote standardization of DLTs to support integration and alignment for interoperability in smart cities. Design science research methodology was adopted based on three use case scenarios which illustrates how IOTA tangle is employs as a DLT for secured standardized communication between physical sensors, devices, and digital platforms in smart city environment. Findings from this article provide exploratory evidence demonstrating the potential uses of IOTA tangle through the developed framework applied for decentralized and centralized digital services. Based on this evidence, this study provides interface integration and alignment strategies to better exploit distributed applications full potential by improving DLT standardization in urban environment.
Blockchain offers a cutting-edge solution for storing medical data, carrying out medical transactions, and establishing trust for medical data integration and exchange in a decentralized open healthcare network setting. While blockchain in healthcare has garnered considerable attention, privacy and security concerns remain at the center of the debate when adopting blockchain for information exchange in healthcare. This paper presents research on the subject of blockchainâs privacy and security in healthcare from 2017 to 2022. In light of the existing literature, this critical evaluation assesses the current state of affairs, with a particular emphasis on papers that deal with practical applications and difficulties. By providing a critical evaluation, this review provides insight into prospective future study directions and advances.
Blockchain technology is a promising technology that attracts popularity among researchers. However, it was first introduced with digital currencies, particularly Bitcoin, but nowadays, it is also known as one of the most frequently used techniques for securing networks. This systematic review research identifies studies that use blockchain for their security challenges. In addition, different fields in blockchain usage, blockchain categorization type, consensus mechanism, smart contract usage, and integration with other software-based algorithms are also investigated. Our results maintain that the Internet of Things (IoT) is the main field in which blockchain provides security.
Intelligent Transportation Systems (ITS) involve integrating information and communication technologies with traffic infrastructure and vehicles to support the development of more sustainable transportation systems. However, ITS face security, reliability, and efficiency challenges in storage and sharing real-time critical data. To address these issues, we propose an architecture based on edge computing and blockchain to enable secure data storage and sharing for ITS. By leveraging edge computing capabilities and blockchain's distributed ledger technology, our architecture enhances data security, ensures data integrity, and improves real-time data processing in ITS. We analyze a smart parking system application scenario, and the results demonstrate a significant reduction in average latency and storage usage, highlighting the positive impact of our solution on enhancing the overall performance and reliability of ITS.
Due to the immutability of blockchain, the integration with big-data systems creates limitations on redundancy, scalability, cost, and latency. Additionally, large amounts of invaluable data result in the waste of energy and storage resources. As a result, the demand for data deletion possibilities in blockchain has risen over the last decade. Although several prior studies have introduced methods to address data modification features in blockchain, most of the proposed systems need shorter deletion delays and security requirements. This study proposes a novel blockchain architecture called Unlichain that provides data-modification features within public blockchain architecture. To achieve this goal, Unlichain employed a new indexing technique that defines the deletion time for predefined lifetime data. The indexing technique also enables the deletion possibility for unknown lifetime data. Unlichain employs a new metadata verification consensus among full and meta nodes to avoid delays and extra storage usage. Moreover, Unlichain motivates network nodes to include more transactions in a new block, which motivates nodes to scan for expired data during block mining. The evaluations proved that Unlichain architecture successfully enables instant data deletion while the existing solutions suffer from block dependency issues. Additionally, storage usage is reduced by up to 10%.
Data in healthcare domain is highly sensitive in nature. Besides, there is need for maintaining integrity of such data. Blockchain technology has emerged to solve the problem of data integrity and non-repudiation with immutable storage in distributed repository. Thus secure data storage and retrieval in cloud environments is made possible using blockchain implementation. There are many existing healthcare systems with blockchain integration found in the literature. However, there is need for a system that supports complete set of operations that are governed by smart contracts. Another important consideration is that end users should be able to operate healthcare system without the need for knowledge of blockchain technology. Towards this end, in this paper, we proposed a Blockchain based secure healthcare data storage and retrieval system known as HealthBlock for cloud computing environments. We defined smart contract with underlying structures and functions using Solidity language for Ethereum blockchain platform. We also proposed and implemented an algorithm known as Healthcare Transactions over Blockchain (HToB). This algorithm supports secure blockchain based data storage and retrieval governed by smart contracts. Our system is evaluated using user-friendly web based client application. The experimental results showed that our system is able to ensure data integrity and non-repudiation besides reaping all benefits of blockchain technology.
This research paper investigates the integration of blockchain technology to enhance the security of Android mobile app data storage. Blockchain holds the potential to significantly improve data security and reliability, yet faces notable challenges such as scalability, performance, cost, and complexity. In this study, we begin by providing a thorough review of prior research and identifying critical research gaps in the field. Android's dominant position in the mobile market justifies our focus on this platform. Additionally, we delve into the historical evolution of blockchain and its relevance to modern mobile app security in a dedicated section. Our examination of encryption techniques and the effectiveness of blockchain in securing mobile app data storage yields important insights. We discuss the advantages of blockchain over traditional encryption methods and their practical implications. The central contribution of this paper is the Blockchain-based Secure Android Data Storage (BSADS) framework, now consisting of six comprehensive layers. We address challenges related to data storage costs, scalability, performance, and mobile-specific constraints, proposing technical optimization strategies to overcome these obstacles effectively. To maintain transparency and provide a holistic perspective, we acknowledge the limitations of our study. Furthermore, we outline future directions, stressing the importance of leveraging lightweight nodes, tackling scalability issues, integrating emerging technologies, and enhancing user experiences while adhering to regulatory requirements.
Blockchain technology is a technology that inherently solves trust issues. It has the character-istics of decentralization, distributed storage, tamper resistance, security, and transparency. It ensures reliable communication between nodes that do not trust each other through consensus mechanisms, smart contracts, and other means. Blockchain stores each transaction data on each transaction node to make the data public and transparent, and generates the data into a blockchain.. As a relatively new distributed database system, blockchain has expanded to many other fields since the initial digital currency, but its development is seriously constrained by problems such as large storage overhead and low query efficiency. In order to find a suita-ble optimization method, select the representative blockchain system Bitcoin, analyze its data structure, data storage and data query processing mechanism, discuss the problems existing in the two functions of storage and query, summarize the existing relevant optimization methods, and look forward to the main research problems of the blockchain system represented by Bitcoin in the future.
Liangmin Wang, Victor S. Sheng, Boris DĂŒdder, Haiqin Wu · 5 authors
Blockchain technology has emerged and evolved as a disruptive technology with the potential to be applied in various fields, including digital finance, healthcare, and the Internet of Things (IoT). Besides being a distributed ledger, blockchain enables decentralized and trusted storage/computation without relying on a central trusted party. However, the growing heterogeneity of blockchain platforms and the expanding range of applications have resulted in escalating security and privacy concerns. These concerns encompass persistent privacy breaches, vulnerabilities in smart contracts, and the âimpossible triangleâ problem. These challenges have emerged as the primary obstacles to the development and seamless integration of blockchain technology with industry applications. To address the security and privacy challenges in blockchain platforms and its applications, numerous researchers have conducted extensive studies in this field by leveraging advanced technologies, including new cryptographic protocols and deep learning techniques. This special issue aims to highlight research perspectives, articles, and experimental studies pertaining to âSecurity and Privacy Issues in Blockchain and Its Applicationsâ. In this special issue, we received a total of nineteen papers, out of which seventeen underwent a rigorous peer-review process. However, two papers were excluded from the peer-reviewed selection because one was submitted in a draft form and the other was voluntarily withdrawn by the authors. Out of the seventeen papers submitted for review, ten were accepted for publication, six were rejected without being transferred, and one was rejected and referred to a transfer service. The exceptional quality of all the submissions played a crucial role in ensuring the success of this special issue. These accepted papers can be classified into two categories, namely blockchain application security and cross-chain interaction security. The papers in the first category focus on analyzing and providing insights into the security of blockchain applications. Their objective is to keep readers informed about the latest trends, developments, challenges, and opportunities in blockchain application security. Moreover, significant research efforts have been dedicated to security analysis and detection in typical blockchain applications. The papers in this category are of Zhou et al., Grybniak et al., Lv et al., Li et al., Gong et al., Xiao et al. and Videira et al. These contributions further enhance our understanding and capability to safeguard blockchain applications from potential security threats. The second category of papers presents novel solutions that target the enhancement of security in cross-system interactions. These papers are of Feng et al., Xu et al. and Yu et al. By addressing the specific challenges associated with cross-system communication, these solutions contribute to the development of robust and secure blockchain networks. A brief presentation of each of the papers in the special issue is as follows. Zhou et al. present WASMOD, a prototype system designed to detect vulnerabilities in WebAssembly (Wasm) smart contracts. WASMOD utilizes a combination of bytecode instrumentation, run-time validation, and grey-box fuzzing techniques to identify integer overflow and stack overflow vulnerabilities. The tool was effectively applied to the EOSIO blockchain, successfully detecting vulnerable smart contracts. Grybniak et al. propose âWaterfall: Gozalandiaâ, a distributed protocol based on the Proof of Stake approach. This protocol enables fast finality, proven safety, and liveness in a network utilizing BlockDAG structures. By employing cross-voting for block ordering, the protocol ensures swift consensus and the ability to detect dishonest behaviors. The protocol assumes the presence of a Coordinating network that holds information about the approved ordering. This Coordinating network serves to significantly enhance security and improve network synchronization in a qualitative manner. Through load testing, the protocol has demonstrated its ability to handle a throughput of 3200â3600 transactions per second, with an average confirmation waiting time of 20 s. Lv et al. propose a graph-based embedding classification method for phishing detection on the Ethereum blockchain. The method involves constructing multiple subgraphs using the transaction records collected from Ethereum and introduces a modified version of Graph2Vec called imgraph2vec. This modified approach aims to learn more meaningful information from the subgraphs. To identify phishing attempts, the Extreme Gradient Boosting (XGBoost) algorithm is utilized. Li et al. introduce BlockDetective, an innovative framework based on GCN that employs a student-teacher architecture to identify fraudulent cryptocurrency transactions. The framework incorporates pre-training and fine-tuning, enabling the pre-trained model (teacher) to effectively adapt to the new data distribution and improve prediction performance. Meanwhile, a lightweight model (student) is trained to provide abstract and high-level information. Experimental results demonstrate that BlockDetective outperforms state-of-the-art methods. Gong et al. propose a novel method called SCGformer, which aims to detect vulnerabilities in smart contracts. This novel method combines the power of a control flow graph (CFG) and a transformer model to enhance the accuracy and effectiveness of vulnerability detection. SCGformer involves constructing the CFGs using the operation codes (opcodes) of smart contracts. By focusing on the opcodes, SCGformer provides a language-agnostic solution, ensuring consistent vulnerability detection regardless of specific language versions. The authors conduct experiments to assess the efficacy of SCGformer, yielding an accuracy rate of 94.36%. Xiao et al. introduce a blockchain-based image copyright protection system named BB-RICP. By leveraging the distributed storage technique of blockchain, BB-RICP aims to solve the vulnerabilities of centralized storage, such as data loss and tampering. The system provides a novel solution for managing the entire lifecycle of copyright. It utilizes spread spectrum watermarking to enable traceability and incorporates GM algorithms and the PBFT consensus algorithm to enhance its functionality and effectiveness. Lastly, to enhance the practicality of the system, they implement a copyright blockchain framework called ICP-Chain and conduct evaluations to assess its security and reliability. Videira et al. propose a solution to tackle the offline puzzle in the implementation of central bank digital currencies (CBDC). This solution involves minting coins with unique serial numbers, which are then stored on a local blockchain within a smartphone or EMV card. The local blockchain is fortified by a two-stage approval architecture that effectively mitigates attacks and facilitates non-repudiation handling. To enhance security, the coins are safeguarded by hardware keys embedded in the microchip and can be continuously mined by the wallet. Feng et al. introduce a novel federated learning framework that leverages a Directed Acyclic Graph (DAG) to enhance interoperability among different blockchains. The framework comprises a shard chain and a main chain, featuring replaceable consensus mechanisms and a weighted context graph to enhance efficiency. The experimental results unequivocally demonstrate the efficacy of the proposed federated framework. Specifically, the framework significantly reduces the global computation requirements while simultaneously increasing the blockchain throughput. Xu et al. introduce ChainKeeper, a cross-chain scheme for governing the chain by chain. ChainKeeper incorporates several key components, including a modular node proxy program, a verifiable node random selection method (VNRS), and a verifiable identity threshold signature method (VITS). These components work together to ensure universality, efficiency, and security throughout the cross-chain process. The scheme is resilient against malicious behaviors and collaborative attacks from both business nodes and supervision nodes. The experimental results demonstrate the effectiveness of ChainKeeper in cross-chain supervision scenarios. Yu et al. present SPRA, a policy-based regulatory architecture designed to regulate blockchain transactions. The architecture comprises four layers: permission layer, regulation layer, bridge layer, and business layer. To facilitate interoperability between these layers, they introduce XRPL, a regulatory policy description language. The regulation layer incorporates JuryBC, a decentralized jury mechanism based on the Shamir threshold secret sharing algorithm and Pedersen commitment. At the business layer, they implement RDShare, a secure and efficient regulatory data sharing mechanism that utilizes attribute-based encryption. All the selected papers in this special issue showcase the continuous advancements in the field of blockchain and its application security. However, it is important to recognize that security and privacy issues in blockchain and its applications continue to pose significant challenges. These challenges serve as a driving force for further research and exploration of new technologies. They highlight the need for ongoing efforts to enhance the security and privacy aspects of blockchain, fostering a more resilient and trustworthy blockchain ecosystem. This work is supported by the National Key R&D Program of China (2020YFB1005500) and the National Natural Science Foundation of China (62372105). The authors would like to express their sincere appreciation to all the contributors who have submitted their scientific findings to this special issue and the anonymous reviewers whose expertise and meticulous work have made this endeavor possible. The authors sincerely hope that this collaborative effort will make a meaningful contribution to the advancement of the field. Lastly, the authors would like to express their utmost appreciation to the editors-in-chief and the editorial office for their unwavering support and guidance throughout this venture. Liangmin Wang received his B.S. degree in computational mathematics in Jilin University, Changchun, China in 1999, and his PhD degree in cryptology from Xidian University, Xi'an, China in 2007. He is a full professor in the School of Cyber Science and Engineering, Southeast University, Nanjing, China. He has been honored as a âWan-Jiang Scholarâ of Anhui Province since November 2013. Now his research interests include data security and privacy. He has published over 70 technical papers at premium international journals and conferences, for example, IEEE/ACM Transactions on Networking and IEEE International Conference on Computer Communications. He has severed as a TPC member of many IEEE conferences, such as IEEE ICC, IEEE HPCC, IEEE Trust-COM. Victor S. Sheng received the master's degree in computer science from the University of New Brunswick, Canada, in 2003, and the PhD degree in computer science from Western University, Ontario, Canada, in 2007. He is an associate professor of computer science, Texas Tech University, and the founding director of the Data Analytics Lab (DAL). His research interests include data mining, machine learning, and related applications. He was an associate research scientist and NSERC postdoctoral fellow in information systems at Stern Business School, New York University, after he obtained his PhD. He is a senior member of the IEEE and a lifetime member of the ACM. He received the test-of-time award for research from KDDâ20, the best paper award runner-up from KDDâ08, and the best paper award from ICDMâ11. He is an area chair and SPC/PC member for several international top conferences and an associate editor for several international journals. Boris DĂŒdder is an associate professor at the department of computer science (DIKU) at the University of Copenhagen (UCPH), Denmark. He is head of the research group Software Engineering & Formal Methods at DIKU. His primary research interests are formal methods and programming languages in software engineering of trustworthy distributed systems, where he is studying automated program generation for adaptive systems with high-reliability guarantees. He is working on the computational foundations of reliable and secure Big Data ecosystems. His research is bridging the formal foundations of computer science and complex industrial applications. Haiqin Wu received her B.E. degree in computer science and Ph.D. degree in computer application technology from Jiangsu University in 2014 and 2019, respectively. She is an associate professor at the Shanghai Key Laboratory of Trustworthy Computing (Software Engineering Institute), East China Normal University, China. Before joining ECNU, she was a postdoctoral researcher in the Department of Computer Science, University of Copenhagen, Denmark. She was also a visiting student in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University, USA. Her research interests include data security and privacy protection, mobile crowdsensing/crowdsourcing, and blockchain-based applications. Huijuan Zhu received her master's degree at School of Computer Science and Communication Engineering in Jiangsu University, Zhenjiang, China in 2010 and her Ph.D. degree at School of Computer and Control Engineering in University of Chinese Academy of Sciences, Beijing, China in 2017. Her research interests include malware detection and machine learning. She is an associate professor in the School of Computer Science and Communication Engineering at Jiangsu University.
The Internet of Things (IoT) technology in various applications used in data processing systems requires high security because more data must be saved in cloud monitoring systems. Even though numerous procedures are in place to increase the security and dependability of data in IoT applications, the majority of outside users can decode any transferred data at any time. Therefore, it is essential to include data blocks that, under any circumstance, other external users cannot understand. The major significance of proposed method is to incorporate an offloading technique for data processing that is carried out by using block chain technique where complete security is assured for each data. Since a problem methodology is designed with respect to clusters a load balancing technique is incorporated with data weights where parametric evaluations are made in real time to determine the consistency of each data that is monitored with IoT. The examined outcomes with five scenarios process that projected model on offloading analysis with block chain proves to be more secured thereby increasing the accuracy of data processing for each IoT applications to 89%.
With the increasing acceptance and utilization of blockchain technology, a multitude of blockchain-based systems have emerged. Consequently, the need for interoperability among these systems has become paramount, particularly in a trustless manner. To enable decentralized and secure cross-chain applications for users, the establishment of a trust-minimized interoperability solution is imperative for homogeneous blockchain-based networks. This paper presents an analysis of the current state and challenges associated with interoperability between blockchain-based systems. Building upon previous research, we propose that the set of blockchain-based networks should be narrowed down based on the same settlement layer for supporting trust-minimized interoperability. Specifically, we concentrate on the cross-rollup functionality between rollups. We have devised and implemented two similar solutions to address the aforementioned interoperability problem, employing a trust-minimized optimistic approach. Through extensive experimentation, we compare our proposed solutions with existing cross-rollup bridges in terms of gas consumption, time complexity, and newly introduced trust assumptions. Our experimental investigations concentrate on the transmission of arbitrary data utilizing non-fungible tokens. The results reveal that one of our proposed solutions offers an optimal approach for cross-rollup communication between optimistic rollups.
Gautami Tripathi, Mohd Abdul Ahad, Gabriella Casalino
Blockchain is a distributed digital ledger technology that has revolutionized businesses, industries, and commerce by eliminating the need for a central storage and control authority. Blockchain presents time-stamped and immutable blocks of data that are not owned by any single entity but rather managed by a group of nodes or computers where each block is secured and linked using cryptographic principles. The immutable and decentralized nature of blockchain has redefined trust, ownership, identity, and financial systems by providing a secure, fast, transparent, and pseudo-anonymous solution. This paper provides a comprehensive review of blockchain technology focusing on the historical background, underlying principles, and the sudden rise in the popularity of blockchain technology. The paper also discusses the various consensus algorithms of blockchain technology. Next, the paper focuses on the various application areas and prospective use cases of blockchain technology with the underlying challenges and issues. Further, the paper presents some unconventional use cases of blockchain technology. The study also reviews state-of-the-art articles to provide a comprehensive overview of the various aspects of blockchain technology in varied domains. The comparison between traditional database systems and blockchain technology is presented, and the appropriate scenarios where blockchain-based solutions may or may not provide the best solutions are also discussed. Further, it discusses some of the most infamous security breaches that impacted the blockchain industry in the recent past.
Geetanjali Rathee, Chaker Abdelaziz Kerrache, Carlos T. Calafate, Mohammed Seghir Halimi
Consumer Electronics (CE) are defined as one of the emerging trends where smart devices, such as refrigerators, smart phones, or house hold devices, generate a huge amount of information by communicating among each other without any human intervention. Yet, the speed of producing such products greatly differs from what would be an optimal utilization and integration of such devices in the environment. In addition, generating and transmitting huge amounts of data within heterogeneous networks produces e-wastage (excessive storage, energy and computational requirements) that further leads to environmental crises, and that can raise severe security problems in terms of network trustworthiness, as the information is conveyed using an open channel, i.e., the Internet. In this regard, most of the solutions reported in the literature are inadequate to handle the aforementioned issues. Hence, in this paper, we propose a lightweight solution to secure the information transmission in one of the most relevant applications of CE, i.e. IIoT networks, using an ML-based Hidden Markov Model (HMM) whereby we compute the degree of trust associated to the different devices based on a blockchain mechanism. In our proposal, an Intrusion Detection System (IDS) is used to inspect the continuous behaviour of each node, and a blockchain network ensures the transparency and security in the network. The proposed technique is validated against existing mechanisms using various security metrics. Extensive simulation results demonstrate that the proposed technique is more effective in terms of malicious node identification in comparison to existing schemes.
In agriculture, soil is a vital element that decides the quality and yield of agricultural produce. Soil consists of various nutrients such as nitrogen (N), phosphorous (P), potassium (K), the potential of hydrogen (pH), and water content. Nitrogen is responsible for building chlorophyll, which helps produce proteins and thus directly contributes to plant growth and development. Phosphorous is needed to develop root systems and flowers, whereas potassium helps increase disease resistance. Each of these play a role in crop cultivation. Thus, in this research paper, considering the fact that soil health will provide farmers with the best selection of crops that are compatible with their farmâs soil nutrients, we propose an algorithm for recommending a set of suitable crops based on various soil attributes. These soil nutrients can be collected in real-time using soil sensors, such as N, P, K, and pH, and humidity sensors. They can be deployed in farms where the cultivation takes place. These sensor readings would then be transferred to the blockchain layer, thereby validating the data and ensuring it is tamper-proof and evident. The crop recommendation model uses data from these sensors in real-time, increasing the resultsâ accuracy. The last stage leads us to display these results via a user dashboard, which helps the farmers to keep in check with their farmâs practices, and their sensor states from remote locations.
Ahmed Alhusayni, Vijey Thayananthan, Aiiad Albeshri, Saleh Alghamdi
Smart devices are connected to IoT networks and the security risks are substantial. Using blockchain technology, which is decentralized and distributed, 5G-enabled IoT networks might be able to tackle security issues. In order to simplify the implementation and security of IoT networks, we propose a multi-level blockchain security model. As part of the multi-level architecture, the communication between levels is facilitated by clustering. IoT networks define unknown clusters with applications that utilize the evolutionary computation method coupled with anatomy simulation and genetic methodologies. Authentication and authorization are performed locally by the super node. The super node and relevant base stations can communicate using local private blockchain implementations. A blockchain improves security and enhances trustworthiness by providing network authentication and credibility assurance. The proposed model is developed using the open-source Hyperledger Fabric blockchain platform. Stations communicate securely using a global blockchain. Compared to the earlier reported clustering algorithms, simulations demonstrate the efficacy of the proposed algorithm. In comparison with the global blockchain, the lightweight blockchain is more suitable for balancing network throughput and latency.
Aaron Werth, Gary Hahn, Raymond Borges Hink, Emilio C. Piesciorovsky · 5 authors
This work involves the development of a device - EmSense (âEmulated Sensorâ) - that emulates a high-resolution sensor for a power grid. The device collects raw current and voltage sensor data which derive from ORNL's signature library. This library is a dataset that ORNL curates from many different sources that include power systems from various utilities. The EmSense packages the data from the library in the form of IEC 61850 Sampled Value (SV) packets and then broadcasts these SV packets on the network. In another mode, EmSense can generate artificial sinusoidal data that appears as waveforms for voltage and current signals. EmSense has an internal algorithm for determining the period of a signal based on the data so that the period can be specified as a variable in the IEC 61850 packets. The purpose of EmSense is to allow for experimentation with the Dark Net Infrastructure where a variety of power line sensors must be represented along with their typical communication traffic. The EmSense device was developed in coordination with the software for receiving and processing the packets in the Distributed Ledger Technology (DLT) framework of the DarkNet Project. This receiving software must have a methodology for dealing with information of high velocity, variety, and volume. Experimenting with EmSense facilitates the development of such software. The results showed that the DLT framework and the trust-anchoring approach managed to process a large flow of traffic even with up to six instances of EmSense device broadcasting data. This was achieved without overfilling packet queues in the memory of the actual hardware of the DLT devices or causing the Central Processing Unit (CPU) of the hardware to be overwhelmed. The DLTs were also able to store the data in a compact and useful form for later analysis and archival purposes.
Sharding is a critical technique that enhances the scalability of blockchain technology. However, existing protocols often assume adversarial nodes in a general term without considering the different types of attacks, which limits transaction throughput at runtime because attacks on liveness could be mitigated. There have been attempts to increase transaction throughput by separately handling the attacks; however, they have security vulnerabilities. This paper introduces Reticulum, a novel sharding protocol that overcomes these limitations and achieves enhanced scalability in a blockchain network without security vulnerabilities.<br/><br/>Reticulum employs a two-phase design that dynamically adjusts transaction throughput based on runtime adversarial attacks on either or both liveness and safety. It consists of `control' and `process' shards in two layers corresponding to the two phases. Process shards are subsets of control shards, with each process shard expected to contain at least one honest node with high confidence. Conversely, control shards are expected to have a majority of honest nodes with high confidence. Reticulum leverages unanimous voting in the first phase to involve fewer nodes in accepting/rejecting a block, allowing more parallel process shards. The control shard finalizes the decision made in the first phase and serves as a lifeline to resolve disputes when they surface.<br/><br/>Experiments demonstrate that the unique design of Reticulum empowers high transaction throughput and robustness in the face of different types of attacks in the network, making it superior to existing sharding protocols for blockchain networks.
Hafiz Burhan Ul Haq, Minahil Irfan, Muhammad Saqlain
For the creation of cryptocurrencies like bitcoin, blockchain is the fundamental technology. Since the development of the steam engine, electricity, and computer technology, there has been a fourth industrial revolution. Blockchain technology is one of the components of this revolution, and it has been used in many sectors, including commerce, banking, and the legal system. In the beginning of this study, we talk about blocks and their many sorts. Following that, cutting-edge blockchain technology applications were covered. In addition, the benefits and drawbacks are also emphasized to help explain the blockchain idea. But there is also discussion on the use of blockchain in 5G.