【Abstract】Blockchain serves as a replicated transactional processing system in a trustless distributed environment. Existing blockchain systems all rely on an explicit ordering step to determine the global order of transactions that are collected from multiple peers. The ordering consensus can be the bottleneck since it must be Byzantine-fault tolerant and can scarcely benefit from parallel execution. In this paper, we propose an ordering-free architecture that makes ordering implicit through deterministic execution. Based on this novel architecture, we develop a permissioned blockchain system NeuChain. A number of key optimizations such as asynchronous block generation and pipelining are leveraged for high throughput and low latency. Several security mechanisms are also designed to make our system robust to malicious attacks. Our geo-distributed experimental results show that NeuChain can achieve 47.2-64.1x throughput improvement over HyperLedger Fabric and 1.6-12.2x throughput improvement over the state-of-the-art high performance blockchains.
【Abstract】Today's large-scale data management systems need to address distributed applications' confidentiality and scalability requirements among a set of collaborative enterprises. This paper presents Qanaat, a scalable multi-enterprise permissioned blockchain system that guarantees the confidentiality of enterprises in collaboration workflows. Qanaat presents data collections that enable any subset of enterprises involved in a collaboration workflow to keep their collaboration private from other enterprises. A transaction ordering scheme is also presented to enforce only the necessary and sufficient constraints on transaction order to guarantee data consistency. Furthermore, Qanaat supports data consistency across collaboration workflows where an enterprise can participate in different collaboration workflows with different sets of enterprises. Finally, Qanaat presents a suite of consensus protocols to support intra-shard and cross-shard transactions within or across enterprises.
【Abstract】The world is facing a growth in the amount and variety of data generated by both users and machines. Despite the exponential increases, the tools and technologies developed to manage these data volumes are not intended to meet security and data protection requirements. Additionally, most of the current big data security systems are offered by a centralized third party, which is vulnerable to many security threats. Blockchain technology plays a significant role by addressing modern technology concerns such as decentralization, non-tampering, trust, data ownership, and traceability, making it great potential to protect personal information. This research presents a new big data security solution empowered by blockchain technology and incorporates fragmentation, encryption, and access control techniques. Our proposed fragmentation algorithm takes into account the data owner's demand for encryption to be added to the fragmentation process. Furthermore, data fragments will be stored in the distributed manner offered by the big data environment, resulting in an additional layer of data protection. In order to achieve an optimal security solution, we aim to enhance big data security with acceptable overhead and avoid the encryption overhead for non-sensitive and low-sensitive data portions. We present the results of our implemented techniques to highlight that the overheads (in terms of computation time) introduced by our solution are negligible relative to its security and privacy gains.
【Keywords】Blockchains; Big Data; Security; Peer-to-peer computing; Encryption; Social networking (online); Streaming media; Big data security; blockchain; fragmentation; access control; auditing
【Abstract】An intelligent military blockchain security management architecture is proposed. Relying on the hierarchical architecture of the data layer, network layer, consensus layer, contract layer and application layer of the blockchain system, the multidimensional detection, intelligent analysis and evaluation, and visual security early warning of abnormal behavior data are carried out by using big data and artificial intelligence technology with real-time collection of various original data information such as nodes, chains, contracts, transactions, accounts and consensus, and security events are quickly located and handled, so as to realize the intelligent linkage closed-loop process of military blockchain security management.
【Abstract】Nowadays, firms are trying to execute and use blockchain technology (BT) for rising the products and service goodness in the supply chain (SC). Based on the specific requirements, the BT can be used in several areas. The BT assets various segments of Supply Chain Management (SCM) with consideration of several effective features that are characterized to be multi-criteria decision making (MCDM) issues with environmental restrictions of uncertainty conditions. This research illustrates the suitability of BT in SCM for various segments that are assessed using a neutrosophic model according to single-valued neutrosophic sets (SVNSs). Also, contributes as an evaluation model that combines neutrosophic set, with MCDM methods of Analytic Hierarchy Process (AHP), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). The proposed study uses the AHP method to generate weights of criteria considering the expert's perspectives. Moreover, uses the neutrosophic theory to handle uncertain situations. The alternatives ranked based on outcomes of applying TOPSIS and VIKOR methods. A case study presents a hierarchical MCDM issue of 7 criteria and 20 sub-criteria with alternative segments assessed. As a result, the medicine segment is recommended to be the best alternative according to the proposed methods of AHP, TOPSIS, and VIKOR while the insurance segment is not recommended by AHP and TOPSIS methods and jewelry segments are not recommended in the VIKOR method.
【Abstract】Software Defined Networking (SDN) is a new network paradigm to address the limitations of vertically integrated conventional networks in context of scalability, Quality of Service, flexibility, and security. SDN isolates the data plane from the control plane and the controller dynamically manages the network activities solely while the switches in the data plane just forward data packets as per the rules set by the controller. With the development of SDN, network security can be done in a more efficient and adaptable way. But the centralized controller, the control-data interface, and the control-application interface are all problems with the way SDN was built from the start. Intruders can use these weaknesses to launch many kinds of attacks to retard the network performance, specifically all layers of SDN architecture are endangered to Distributed Denial of Service (DDoS) attacks. In this paper, we discuss the popular DDoS attack detection approaches in SDN such as statistical, blockchain, machine learning and deep learning.
【Keywords】Distributed Denial of service (DDoS); Software Defined Networks (SDN); Blockchain; Entropy; Machine Learning (ML); Deep Learning (DL); Network Security
【Abstract】Nowadays, System-on-Chip (SoC) components are found everywhere in all kinds of smart devices. Each System-on-Chip contains many different blocks that provide specific functionalities, such as WiFi or Bluetooth connectivity. Whereas integrating each such block in a SoC typically requires paying some royalties, not all blocks are necessary for all applications, or throughout a device's lifecycle. Moreover, it is not possible to manufacture a specific SoC for each application. Significant advantages are therefore expected to be gained by enabling trustworthy remote SoC reconfiguration throughout their life cycles. A few approaches attempting to address this challenge have been proposed in the literature. They are typically based on Blockchain technology in order to support decentralization without relinquishing trust. Reviewing these approaches lead us to identify a potential flaw in the proposed protocols. Indeed, a SoC should be able to trust Blockchain information that it is given, without requiring any centralization. In order to validate our suspicions, we propose in this paper to use Verifpal: a cryptographic protocol verification tool that works from textual protocol models. We use it in a slightly unorthodox way in order to model the trust relationships in one of the approaches from the literature, and to verify it. The results show that, under some assumptions, a flaw is indeed present. We propose and model several possible fixes, and present their respective limitations.
【Abstract】Data provenance is a basic requirement for trusted data management in the era of big data. Before the emergence of blockchain technology, data provenance mainly used a centralized database to store data records, log records, etc., to facilitate subsequent audit tracking, but database has the security problem of data tampering. After the emergence of blockchain technology, researchers have conducted a lot of research on trusted data provenance in the Internet of Things (IoT), product supply chain, medical health and other fields based on the characteristics of blockchain decentralization, tamper resistance, and traceability,etc., to ensure the security and trustworthiness of data provenance results. This paper will sort out the research on the use of blockchain technology for data provenance in different fields in recent years, and analyze the similarities and differences between existing blockchain based data provenance methods as a whole. Finally, the possible challenges in data provenance based on blockchain technology are pointed out and the possible solutions are given.
【Abstract】An accumulator is a function that hashes a set of inputs into a short, constant-size string while preserving the ability to efficiently prove the inclusion of a specific input element in the hashed set. A concrete accumulator is constructed by using strong RSA assumption. Thanks to their practical features, accumulators are used in various protocols such as zero-knowledge proofs, group signatures, and blockchain. However, lattice-based accumulators are not as well studied as the strong RSA assumption. In 2019, Ling et al. constructed a lattice-based accumulator that is enable to update the member in the list, called LLNW in this paper. However, the update algorithm of the LLNW scheme is not complete, since it requires recalculation to any member regardless of whether or not the member is updated. In this paper, we propose an efficient update algorithm, called EfficientAccWitUpdate, to LLNW, which enables us to update members more efficiently than that in LLNW. In our method, only a member who updates requires recalculation. Specifically, the number of multiplications required for updating in EfficientAccWitUpdate is 1/2 of LNWX, and the number of additions required for updating in EfficientAccWitUpdate is nk+1/2nk-1 of LNWX. Consequently, by incorporating the EfficientAccWitUpdate accumulator scheme into the zero-knowledge protocol, group signature, and blockchain, it is possible to realize a more efficient application.
【Abstract】Internet of Things enables devices to communicate, collect and exchange data with the network. As the number of IoT devices keeps growing, the volume of data they produce is also increasing exponentially. Given the feature of limited computing and storage resources of IoT, it is inevitable to store data in the cloud for better services. However, for users to effectively and efficiently inspect those data over the cloud is a critical and open problem. Most public integrity auditing over the cloud schemes requires the user to do a sheer amount of preprocessing work on the local devices, which is unsuitable for IoT devices. With the development of edge computing extending cloud computing, it can provide computing capability for resource-constrained devices in close geographic proximity. In this paper, we design an auditing scheme based on secure computation outsourcing assisted by edge computing, in which the data preprocessing work can be offloaded to the edge server. The experiments show that it reduces the computing load on the devices and improves the efficiency of task processing.
【Abstract】The consensus mechanism plays a pivotal role in guaranteeing the security and consistency of blockchain systems and substantially affects system performance. However, an increasing number of blockchain nodes degrade the consensus performance dramatically because of the high communication complexity in traditional consensus mechanisms. In this paper, we propose NS-consensus, a secure node-sampling blockchain consensus mechanism reducing the communication complexity significantly. The key novelty lies in the sampling of blockchain nodes so that the leader only needs to interact with the sampling nodes in each consensus epoch. However, NS-consensus imposes two challenges in determining an optimal sample size and denying malicious proposals. To address the challenges, we determine the sample size under the constraints of a confidence level and a margin of error to enhance communication efficiency without compromising system security. Furthermore, we design a mechanism to enable the leader to interact with all blockchain nodes in the last consensus phase, ensuring the denial of malicious proposals. The extensive experimental results indicate that NSconsensus outperforms the state-of-the-art with up to 175.1% higher system throughput and 79.9% lower time overhead in the sampling phases.
【Abstract】It is increasingly popular to utilize the wisdom of the crowd for knowledge discovery and monetization. Most of the existing knowledge marketplaces in crowdsensing are implemented by a third-party platform, which may compromise users' rights and be vulnerable to incurring attacks in practice. To eliminate the untrustworthy behaviors of the third party and improve tolerance for the attacks, some blockchain-based knowledge marketplaces in crowdsensing have been proposed. However, the existing blockchain-based knowledge marketplaces fail to simultaneously guarantee privacy (i.e., data privacy and task privacy) and quality awareness. In this paper, we design a blockchain-based privacy-preserving quality-aware knowledge marketplace (PQKM) based on truth discovery, secure K-nearest neighbor computation, matrix decomposition, and data perturbation. PQKM privately calculates users' data quality and automatically rewards users based on their data quality. Detailed security analysis demonstrates that PQKM can preserve data privacy and task privacy during knowledge discovery and monetization. Extensive experiments are conducted on the open real-world dataset to show that PQKM has acceptable efficiency and affordable performance.
【Abstract】In January 2017, a truck crossed the border between Spain and France for the first time using an e-CMR: An electronic version of the primary transport document required for inter-European logistics. Since that crossing, researchers and logistic organizations have proposed a large number of ideas to further digitize Europe's supply chain. Many of these ideas involve blockchains, but not all of them validate the data that is posted to them. As a result, participants can make illegitimate claims: Even though the blockchain enables transparency and immutability of the data stores, it does not ensure veracity. We provide several examples of works about information sharing in the supply chain that do not perform such validation. One work that does use the blockchain's validation functionality is DEFEND. DEFEND addresses customs agencies' lack of information for international freight inspection by tracking shipping containers throughout their journey. As containers pass from one operator to another, the blockchain participants ensure that containers are not doubly spent. In this work, we propose an extension of DEFEND, in which we further extend the capabilities for validation. Moreover, we provide actual cryptographic protocols to preserve participants' privacy while DEFEND only described privacy on a high level. Finally, by making a more fine-grained distinction between different actors in the chain, we model the entire supply chain from buyer to seller. As a result, the buyer and seller can now track the respective package's whereabouts through each leg of its journey.
【Abstract】Aiming at the cross-chain problems faced by financial transactions, study the cross-chain communication protocols of the financial-oriented autonomous panda model and golden monkey model, and study the construction of a new scalable and credible multi-chain model that supports homogeneous blockchains and heterogeneous blockchains. The models and protocols that support financial transactions in the blockchain environment need to be able to meet the SSL or SET security protocols similar to traditional Internet transactions, and meet various requirements such as transaction integrity, reliability, and privacy protection.
【Abstract】Future communication systems are trending to embrace an open and collaborative ecology for a rising number of edge services and applications, enabling the evolutions of multiple wireless ecosystems such as the Internet of things (IoT). The collaborations among multi-party IoT users, devices, and infrastructure require further designs in terms of security, trust, and efficiency. Blockchain is considered a promising solution to facilitate trusted multi-party collaborations, enhance security, and protect privacy in the IoT. However, the research on IoT-friendly blockchains is still facing a number of challenges due to the heterogeneity and limited capabilities of IoT devices. In this paper, we propose a hierarchical blockchain consensus combining practical Byzantine fault tolerance and a game-based node selection mechanism (GaS-PBFT). GaS-PBFT enables a logical two-layer consensus network structure, groups heterogeneous IoT participants into multiple collaborating consensus groups, and imposes an efficient and fair game on each group for selecting block generators of the IoT blockchains. Finally, we conduct comprehensive simulations to show the performance of the proposed GaS-PBFT consensus in terms of consensus latency, transaction speed, node capacity, and security.
【Abstract】There is a significant rise in vehicle-to-vehicle (V2V) communication for intelligent transportation systems such as reducing road accidents, traffic congestion, and optimal route planning. The main objective of the V2V communication is to provide real-time monitoring data from vehicles sensors to other vehicles. However, the attackers can exploit this communication by forging the controller area network (CAN) protocol and injecting malicious traffic. In this context, the vehicles mislead by false update messages and alerts. To overcome this issue, this paper presents the artificial intelligence (AI) and blockchain-based proposed architecture on a 6G network. The proposed architecture is examined with a car hacking dataset, wherein the sensors of vehicles are communicating with each other for data sharing. For that, we have adopted an AI algorithm, i.e., random forest (RF), to classify normal and malicious data traffic. Further, edge nodes are considered to reduce the computation of AI algorithms and faster accessibility of vehicular data. Furthermore, incorporating inter planetary file system (IPFS) and a 6G network makes the proposed architecture cost-effective and scalable. Finally, the architecture is evaluated against performance metrics such as accuracy, latency, and scalability. The results demonstrate that the RF surpasses the other algorithms in terms of accuracy and achieves 97% accuracy.
【Abstract】In the fog computing network (FCN), due to the characteristics of user dispersion and real-time data, the user privacy is an urgent issue to be solved. Federated learning is considered as a potential solution to avoid data leakage between fog nodes and remote clouds. In this paper, a malicious models-based federated learning framework is proposed, in which the dual-layer blockchain contains the main-blockchain and the directed acyclic graph chain is enabled in the network structure to ensure the data security. Moreover, in federated learning, the reliability of local models cannot be guaranteed, when there are malicious models, the global model accuracy will be decreased. An isolation forest-based malicious model detection algorithm is proposed, which could filter malicious local models and perform global aggregation through the Stochastic Gradient Descent algorithm to ensure the security of the global model. Finally, the simulation results show the effectiveness of the proposed algorithm.
【Abstract】Federated learning implements decentralized machine learning tasks without exposing users' private data. However, in practical scenarios, intelligent devices data pertain to different fields are non-independent and identically distributed (non-IID), which leads to a decrease in the accuracy of the global model. In addition, if there are untrusted devices participated in federated learning, the global model accuracy will be decreased. To address the above-mentioned issues, in this paper, we propose a blockchain-enabled hierarchic cluster-based federated learning in edge computing framework to improve the accuracy of the global model and ensure the local model credibility. Firstly, we propose the hierarchic cluster-based federated learning (HCFL) algorithm, which realizes hierarchically aggregation based on user cosine similarity to improve global model accuracy. Moreover, blockchain technology is enabled in the proposed HCFL algorithm to verify the local model gradient from IDs before global aggregation. Moreover, incentive mechanism is proposed to dynamically adjust reward of IDs for promote IDs train trusted models. Finally, simulation results demonstrate the efficiency and performance of the blockchain-enabled hierarchic cluster-based federated learning framework.
【Abstract】The space-air- ground- aqua integrated network will become the basic form of the next generation network. Various technologies, including artificial intelligence, big data, cloud computing, edge computing, etc., will be deeply integrated into the network to form an integrated intelligent network of land, sea, air and space. In this article, we will present the vision for the development of the space-air-ground-aqua integrated intelligent network and describe its main features. We put forward a network architecture which integrated sub-networks of space, air, land and sea while emphasizing network interconnection, resources sharing, cooperative control and service reuse. We also discussed several promising technologies, including the THz, free space optical communication, software defined network, network function virtualization, edge intelligent, digital twins, physical layer security and blockchains.
【Abstract】Rust is an emerging programming language designed for secure system programming that provides both security guarantees and runtime efficiency and has been increasingly used to build software infrastructures such as OS kernels, web browsers, databases, and blockchains. To support arbitrary low-level programming and to provide more flexibility, Rust introduced the unsafe feature, which may lead to security issues such as memory or concurrency vulnerabilities. Although there have been a significant number of studies on Rust security utilizing diverse techniques such as program analysis, fuzzing, privilege separation, and formal verification, existing studies suffer from three problems: 1) they only partially solve specific security issues but lack comprehensiveness; 2) most of them require manual interventions or annotations thus are not automated; and 3) they only cover a specific phase instead of the full lifecycle. In this perspective paper, we first survey current research progress on Rust security from 5 aspects, namely, empirical studies, vulnerability prevention, vulnerability detection, vulnerability rectification, and formal verification, and note the limitations of current studies. Then, we point out key challenges for Rust security. Finally, we offer our vision of a Rust security infrastructure guided by three principles: Comprehensiveness, Automation, and Lifecycle (CAL). Our work intends to promote the Rust security studies by proposing new research challenges and future research directions.
【Abstract】The increased use of Internet of Things (IoT) devices -from basic sensors to robust embedded computers- has boosted the demand for information processing and storing solutions closer to these devices. Edge computing has been established as a standard architecture for developing IoT solutions, since it can optimize the workload and capacity of systems that depend on cloud services by deploying necessary computing power close to where the information is being produced and consumed. However, as the network scale in size, reaching consensus becomes an increasingly challenging task. Distributed ledger technologies (DLTs), which can be described as a network of distributed databases that incorporate cryptography, can be leveraged to achieve consensus among participants. In recent years DLTs have gained traction due to the popularity of blockchains, the mostwell known type of implementation. The reliability and trust that can be achieved through transparent and traceable transactions are other key concepts that bring IoT and DLT together. We present the design, development and conducted experiments of a proof-of-concept system that uses DLT smart contracts for efficiently selecting edge nodes for offloading computational tasks. In particular, we integrate network performance indicators in smart contracts with a Hyperledger Blockchain to optimize the offloading on computation under dynamic connectivity solutions. The proposed method can be applied to networks with varied topologies and different means of connectivity. Our results show the applicability of blockchain smart contracts to a variety of industrial use cases.
【Abstract】A high level of scalability is needed to support the large-scale Internet-of-Things (IoT) networks. To address the issue of distributed trust in different IoT devices, blockchain technology can be effectively used to safely manage IoT data due to its ability to provide transactions traceability and security. However, massive real-time IoT application data has brought huge challenges to the scalability of the integration framework of blockchain and IoT. This paper proposes a nested-chain architecture, which consists of one main chain and multiple sub chains to address the aforementioned challenges. The main chain stores identity credential used for distributed identity (DID) management, while the sub chain stores the IoT data. A notary module that involves access nodes from both chains is designed for cross-chain transactions. In addition, considering the transaction information, node characteristics, and network status, we further introduce a node selection algorithm based on Graph Convolutional Network (GCN), which can effectively reduce the cost of cross-chain communications. We implement and evaluate a prototype of our framework on the Hyperledger Fabric platform to demonstrate its feasibility and superiority. The analyzed results have shown that our proposed framework outperforms traditional schemes, by reducing system latency up to 23.2% and increasing system throughput up to 12.5%.
【Abstract】The supervision of supply disruptions, expiry, and fake products are just a few examples of crucial healthcare supply chain operations. Due to the competitive nature of the healthcare supply chain, which is vulnerable to paradoxical situation and unnecessary endeavors that may jeopardize patient safety and negatively affect medical outcomes, it is difficult to implement and carry out these operations in a reliable, successful, convenient, and checkable manner. A developing technology called blockchain and the Internet of Medical Things (IoMT) can provide a workable answer to these problems. They offer a great solution to monitor and trace things. This paper identifies the main problems with healthcare supply chain processes and shows how IoT blockchain technology might help solve these problems.
【Abstract】In the paper we focus on a promising research problem of data trading, under the scenario that data items can be reproduced easily and inexpensively. Apart from a Bayesian optimal mechanism based data trading approach, we also propose a prior-free data trading approach to organize the data trading process between selfish data owners and share-averse data consumers, with the goal of maximizing revenue of data owners and meanwhile determining the optimal number of data copies. Rigorous theoretical analysis and extensive experiment results are offered to verify the effectiveness of proposed methods in terms of sum of valuations, revenue, individual rationality and incentive compatibility.
【Abstract】Compared with public blockchain, consortium blockchain is more secure and controllable deployed in an enterprise scenario. Byzantine fault tolerance (BFT) consensus is widely applied in consortium blockchain. Although PBFT is the most classic practical BFT consensus with message complexity O(n(2)), it still faces some security threats and has low consensus efficiency. To address these issues, we propose a secure and trusted BFT ((SBFT)-B-2) consensus based on trusted committees. (SBFT)-B-2 generates a trusted anonymous number using trust execution environment (TEE) for each server node and selects committees by pseudo-random algorithm. (SBFT)-B-2 can efficiently reach consensus by the committees with an O(m*n) message complexity. In addition, correctness analysis proves that (SBFT)-B-2 can resist more attacks than traditional BFT consensus and tolerate 1/2 byzantine server nodes. Results further demonstrate the efficiency of the simulated (SBFT)-B-2 implementation.
【Abstract】Despite the growing interest in blockchain technology, the scalability of blockchain storage has become a major issue for applications that require large amounts of on-chain data. In this paper, we propose a novel scalable storage scheme for consortium networks to manage the storage capacity required by data-rich blockchain applications. We establish network nodes as super peers or regular peers, where super peers can maintain old blockchain data in the form of historical blockchains. Regular peers maintain only the latest blockchain data stored in the current blockchain, but they can access any data in the historical blockchains by making queries to the super peers. We present procedures to build a historical blockchain and retrieve data from the historical blockchains and the current blockchain in a concurrent manner. Experimental results show that our scalable storage scheme using historical blockchains is feasible and effective in accessing and sharing healthcare data with image files.
【Abstract】IOTA has emerged as a promising and feeless decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications with high-performance transaction rates and incremental scalability. To support micropayments of IoT devices, IOTA has abandoned the original blockchain reward mechanism while IOTA nodes voluntarily contribute resources to maintain network stability. However, removing the mining rewards results in the resource cost of generating IOTA ledgers (known as the Tangle) being borne only by IOTA nodes. With the continuous expansion of the IOTA network, cost consumption is increasing. Thus, the inability to effectively reduce the cost of Tangle generation would lead to people being reluctant to dedicate resources to IOTA for maintaining the network robustness. In this paper, for the first time, we present a full-fledged transaction cost optimization scheme for IOTA, called Tangless, which can assist IOTA nodes in effectively reducing the Tangle generation cost while maintaining the strong robustness of the IOTA network. By using our proposed scheme, each IOTA node can effectively formulate the threshold of transaction approval rate in real time, maintaining the stability of the IOTA network with the optimal computational cost. We harness Lyapunov optimization theory to design a computational optimization algorithm for minimizing the total cost of nodes in IOTA. Then, we resort to large deviations theory to devise an optimized transaction rate control algorithm to further eliminate orphan Tangles that waste computational costs. Comprehensive theoretical analysis and simulation experiments confirm the effectiveness and practicability of our proposed scheme.
【Abstract】Blockchain technology brings numerous varieties of applications, and within them, the electric energy area stands out. To apply this technology in the sector, it is necessary to understand its characteristics and the needs of users. This paper presents the main characteristics of blockchain technology, a survey carried out with users of shared generation, and, using the data collected together with a market research, a business model was developed with short, medium and long expectations.
【Abstract】Computer systems at the security and management level play a role in the era called Digital health. Thus, security processes in the medical field benefit health service providers, their administrators, and registered patients with an electronic medical record (EHR) since the information belongs to them. Smart contracts, in conjunction with blockchain technology, are a way to work and improve these security components associated with EHR. This manuscript describes different proposals presented by researchers where smart contracts are used for authentication and entry into a system, as well as a brief comparison between the proposed algorithms, their performance in terms of time and concurrency, and the security tests carried out to confirm system security. This paper also verifies the open issues and proposed future works described by the different authors.
【Abstract】The latest, modern security camera systems record numerous data at once. With the utilization of artificial intelligence, these systems can even compose an online attendance register of students present during the lectures. Data is primarily recorded on the hard disk of the NVR (Network Video Recorder), and in the long term, it is recommended to save the data in the blockchain. The purpose of the research is to demonstrate how university security cameras can be securely connected to the blockchain. This would be important for universities as this is sensitive student data that needs to be protected from unauthorized access. In my research, as part of the practical implementation, I therefore also use encryption methods and data fragmentation, which are saved at the nodes of the blockchain. Thus, even a DDoS (Distributed Denial of Service) type attack may be easily repelled, as data is not concentrated on a single, central server. To further increase security, it is useful to constitute a blockchain capable of its own data storage at the faculty itself, rather than renting data storage space, so we, ourselves may regulate the conditions of operation, and the policy of data protection. As a practical part of my research, therefore, I created a blockchain called UEDSC (Universities Data Storage Chain) where I saved the student's data.
【摘要】自2021年以来，元宇宙在学界被瞬间引爆，国内外研究成果快速涌现。本文结合定性与定量方法分析“Ei Compendex Web”“Web of Science核心合集”和中国知网元宇宙主题论文，厘清国内外元宇宙研究状态。研究发现：元宇宙在国内外的研究虽有重叠但差异较大；元宇宙在国内外均处于研究初期，成果及高产作者少，核心作者群及稳定合作团队均未出现，期刊、基金都少关注元宇宙研究；国外研究早于国内且持续性更久，但国内热度高于国外，国内期刊接受度也高于国外；研究领域与研究热点内容国内外有所不同，国外更偏好自然科学及工科应用领域，尤其是计算机学科，而国内偏好传播学，国内学科集中度高于国外。为推动我国元宇宙研究，提升我国元宇宙研究的国际影响力，应实施一系列举措鼓励与引导元宇宙研究，包括培育研究团队、增设基金项目尤其是企业基金、鼓励期刊选稿用稿等。
