A tecnologia blockchain é uma espécie de banco de dados ou um livro razão, no qual é possível inserir e transmitir informações de uma forma totalmente segura, rápida e transparente, não centralizando a informação em apenas um ponto. Também conhecida como “<strong>protocolo de confiança</strong>“, essa tecnologia foi criada em 2008 por Satoshi Nakamoto<sup>1</sup>, sendo, na época, a principal inovação no mundo tecnológico do bitcoin, mas não se confunde com a criptomoeda, pois essa tecnologia também pode ser utilizada nos mais diversos segmentos, como na educação, alimentos, automobilístico, marketing, saúde, e também no direito. Essa nova tecnologia propõe imutabilidade, transparência e descentralização como principal medida de segurança, funcionando como se fosse um livro razão, público, sem intervenção de terceiros. É uma base de dados distribuída que guarda um registro de transações definitivas e a prova de violação, não permitindo alterações, pois armazena informações em blocos que dependem de outros blocos seguintes e posteriores, formando uma cadeia de blocos. Ademais, essas informações não ficam em um computador centralizado, como habitualmente ocorre nos armazenamento de dados padrões pelo mundo, mas sim em milhares de computadores, cada um com seu próprio backup. Dessa forma não permitindo falhas que comumente poderiam ocorrem em uma centralização dos dados, pois se um nó (computador) deixar a rede, os demais conectados já teriam parte daquele bloco para compor a ausência deste. Isso faz com que todas as informações estejam sempre disponíveis de forma segura, pois um atacante (hacker) não conseguiria modificar as informações de toda uma cadeia de blockchain.
Marc Pilkington, Erdita Kumaraku, Kejsi Bushi, Katia Haveri
Albania is a small country of the West Balkans situated in Southeast Europe still in the early stages of distributed ledger technology (DLT) adoption. In this research note, we begin to investigate the cryptocurrency regulatory framework and propose a national blockchain roadmap for the country. Albania was one of the first European nations to elaborate a cryptocurrency regulatory framework aimed at safeguarding users from the dangers of fraud and imposing sanctions in situations of misuse. Our proposed national blockchain roadmap includes emerging priorities such as licensed entities, digital divide reduction, remittances digitisation, Ethereum 2.0, blockchain FDI, e-voting, and the quadruple helix system.
During the COVID-19 pandemic, the uncertainty in the markets was also reflected in the demand for cryptocurrencies. This study aims to visually present the bibliometric analyzes of empirical studies on cryptocurrencies during the COVID-19 pandemic period (between 2020-2022). For this purpose, VOSviewer software was used to perform a bibliometric analysis of 30 selected studies. According to the results obtained, it is seen that the selected studies are mostly scanned in the SCOPUS and SSCI indexes of the journals published. Most studies were conducted in Malaysia, followed by Pakistan and Spain. 7 studies were conducted in Malaysia and 3 studies each in Pakistan and Spain. In the studies, it was seen that the technology acceptance model, planned behavior theory, and unified theory of acceptance and use of technology were used the most, respectively. Structural equation modeling was used in 23 studies. When the variables used were examined, it was understood that the most used variables were the intention, risk, trust, and attitude. Considering the uncertainties in the pandemic period and the characteristics of cryptocurrencies, it is thought that the variables used to make significant contributions to the literature and relevant persons.
BACKGROUND: A clinical trial management system (CTMS) is a suite of specialized productivity tools that manage clinical trial processes from study planning to closeout. Using CTMSs has shown remarkable benefits in delivering efficient, auditable, and visualizable clinical trials. However, the current CTMS market is fragmented, and most CTMSs fail to meet expectations because of their inability to support key functions, such as inconsistencies in data captured across multiple sites. Blockchain technology, an emerging distributed ledger technology, is considered to potentially provide a holistic solution to current CTMS challenges by using its unique features, such as transparency, traceability, immutability, and security. OBJECTIVE: This study aimed to re-engineer the traditional CTMS by leveraging the unique properties of blockchain technology to create a secure, auditable, efficient, and generalizable CTMS. METHODS: A comprehensive, blockchain-based CTMS that spans all stages of clinical trials, including a sharable trial master file system; a fast recruitment and simplified enrollment system; a timely, secure, and consistent electronic data capture system; a reproducible data analytics system; and an efficient, traceable payment and reimbursement system, was designed and implemented using the Quorum blockchain. Compared with traditional blockchain technologies, such as Ethereum, Quorum blockchain offers higher transaction throughput and lowers transaction latency. Case studies on each application of the CTMS were conducted to assess the feasibility, scalability, stability, and efficiency of the proposed blockchain-based CTMS. RESULTS: A total of 21.6 million electronic data capture transactions were generated and successfully processed through blockchain, with an average of 335.4 transactions per second. Of the 6000 patients, 1145 were matched in 1.39 seconds using 10 recruitment criteria with an automated matching mechanism implemented by the smart contract. Key features, such as immutability, traceability, and stability, were also tested and empirically proven through case studies. CONCLUSIONS: This study proposed a comprehensive blockchain-based CTMS that covers all stages of the clinical trial process. Compared with our previous research, the proposed system showed an overall better performance. Our system design, implementation, and case studies demonstrated the potential of blockchain technology as a potential solution to CTMS challenges and its ability to perform more health care tasks.
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors. In this paper, we focus on predicting the pump probability of all coins listed in the target exchange before a scheduled pump time, which we refer to as the target coin prediction task. Firstly, we conduct a comprehensive study of the latest 709 P&D events organized in Telegram from Jan. 2019 to Jan. 2022. Our empirical analysis reveals some interesting patterns of P&Ds, such as that pumped coins exhibit intra-channel homogeneity and inter-channel heterogeneity. Here channel refers a form of group in Telegram that is frequently used to coordinate P&D events. This observation inspires us to develop a novel sequence-based neural network, dubbed SNN, which encodes a channel's P&D event history into a sequence representation via the positional attention mechanism to enhance the prediction accuracy. Positional attention helps to extract useful information and alleviates noise, especially when the sequence length is long. Extensive experiments verify the effectiveness and generalizability of proposed methods. Additionally, we release the code and P&D dataset on GitHub: https://github.com/Bayi-Hu/Pump-and-Dump-Detection-on-Cryptocurrency, and regularly update the dataset.
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Because of its many advantages, big data has been extending to various domains of science, health, education, and commerce. Despite its many applications, big data sharing typically suffers from some key issues, such as user control, lack of incentives, cost, and the right of data. This paper proposes a decentralized big data sharing prototype to improve the applications and services of big data. The method makes use of Ethereum blockchain and related technologies to systematically recommend the implementation guidelines. The research provides a detailed description of the design and implementation of each sublayer of a big data system. As the method is based on blockchain technology, the key technical points are properly addressed in each of the layers. For evaluation, relevant data were collected, and functional testing was performed. A comparison was performed about the sharing frequency and blockchain consensus performance of similar platforms. The dual mining node of the proposed prototype succeeded in processing 1366 blocks and 300 messages. A comparatively satisfactory file access time in the range of 10 m to 20 s and file transmission time between 100 m and 200 s were achieved. The results obtained show that this prototype can effectively verify the feasibility of the model, the layered architecture, and the related sharing mechanism. For the functional and performance testing, practical projects were implemented and evaluated. The promising results obtained testify that the research offers a theoretical background for innovative research in the domain and specialized guidelines for practical implementation.
Thiago Bulhões da Silva Costa, Lucas Shinoda, Ramon A. Moreno, José Eduardo Krieger · 5 authors
Background The importance of blockchain-based architectures for personal health record (PHR) lies in the fact that they are thought and developed to allow patients to control and at least partly collect their health data. Ideally, these systems should provide the full control of such data to the respective owner. In spite of this importance, most of the works focus more on describing how blockchain models can be used in a PHR scenario rather than whether these models are in fact feasible and robust enough to support a large number of users. Objective To achieve a consistent, reproducible, and comparable PHR system, we build a novel ledger-oriented architecture out of a permissioned distributed network, providing patients with a manner to securely collect, store, share, and manage their health data. We also emphasize the importance of suitable ledgers and smart contracts to operate the blockchain network as well as discuss the necessity of standardizing evaluation metrics to compare related (net)works. Methods We adopted the Hyperledger Fabric platform to implement our blockchain-based architecture design and the Hyperledger Caliper framework to provide a detailed assessment of our system: first, under workload, ranging from 100 to 2500 simultaneous record submissions, and second, increasing the network size from 3 to 13 peers. In both experiments, we used throughput and average latency as the primary metrics. We also created a health database, a cryptographic unit, and a server to complement the blockchain network. Results With a 3-peer network, smart contracts that write on the ledger have throughputs, measured in transactions per second (tps) in an order of magnitude close to 102 tps, while those contracts that only read have rates close to 103 tps. Smart contracts that write also have latencies, measured in seconds, in an order of magnitude close to 101 seconds, while that only read have delays close to 100 seconds. In particular, smart contracts that retrieve, list, and view history have throughputs varying, respectively, from 1100 tps to 1300 tps, 650 tps to 750 tps, and 850 tps to 950 tps, impacting the overall system response if they are equally requested under the same workload. Varying the network size and applying an equal fixed load, in turn, writing throughputs go from 102 tps to 101 tps and latencies go from 101 seconds to 102 seconds, while reading ones maintain similar values. Conclusions To the best of our knowledge, we are the first to evaluate, using Hyperledger Caliper, the performance of a PHR blockchain architecture and the first to evaluate each smart contract separately. Nevertheless, blockchain systems achieve performances far below what the traditional distributed databases achieve, indicating that the assessment of blockchain solutions for PHR is a major concern to be addressed before putting them into a real production.
Bo Zhao, Chenhan Shangguan, Xiaoyan PENG, Yang AN · 6 authors
In order to solve the problems of low detection accuracy and high false positive rate of traditional smart contract vulnerability detection methods and less consideration of bytecode level smart contract features in neural networks, a smart contract bytecode vulnerability detection method based on semantic perception graph neural network was proposed. First, in order to generate the control flow graph, the basic blocks divided by the smart contract bytecode were used as the nodes, and the call relationship between the basic blocks was extracted from the bytecode as the edges. Then, control flow graph is transmitted into the graph convolutional network for training to obtain the feature representation of the graph nodes; Afterwards, the contract bytecode instruction sequence is segmented, transformed into a word vector, embedded into a low-dimensional space and transmitted to a long short-term memory network for training. Then, the vector representation of bytecode semantic information was obtained. Finally, the generated node features and semantic features were spliced and transmitted to the full connection layer for dimensionality reduction. Combined with semantic information and node features, the vulnerability detection was carried out for smart contracts. The real smart contracts in public dataset were used for training and testing, and verified in two types of vulnerability classification datasets through traditional methods and artificial tags. The method proposed in this paper was compared with three traditional smart contract vulnerability detection tools and one smart contract vulnerability detection method based on neural network. The experimental results showed that the proposed network greatly improves the performance of network in terms of various indicators, and detects the contracts with vulnerabilities which are not detected by the other four methods. It shows that adding the bytecode semantic information to graph neural network can effectively improve the detection accuracy and reduce the false alarm rate.
Based on blockchain technology,Ethereum Solidity smart contract as a computer protocol is designed to spread,verify,or execute contracts in an informative way,and it provides a foundation for various distributed application services.Although implemented for less than six years,its security problems have frequently broken out and caused substantial financial losses,which attracts more attention in the security inspection research.This paper firstly introduces some specific mechanisms and operating principles of smart contracts based on Ethereum related techniques,and analyzes some smart contract vulnerabilities occurring frequently and deriving from the characteristics of smart contracts.Then,this paper explains the traditional mainstream smart contract vulnerability detecting tools in terms of symbolic execution,fuzzing,formal verification,and taint analysis.In addition,in order to cope with the endless new vulnerabilities and the need to improve the efficiency of detection,vulnerabilities detection based on machine learning in recent years is classified and summarized according to the various ways of problem transformation in three perspectives including text processing,non-Euclidean graph and standard image.Finally,this paper proposes to formulate more extensive and accurate standardized information database and measurement indicators towards the insufficiency of the detection methods in two directions.
Blockchain is a technology that has desirable features of decentralization, autonomy, integrity, immutability, verification, fault-tolerance, anonymity, auditability, and transparency. In this paper, we first carry out a deeper survey about blockchain technology, especially its history, consensus algorithms' quantitative comparisons, details of cryptography in terms of public key cryptography, Zero-Knowledge Proofs, and hash functions used in the blockchain, and the comprehensive list of blockchain applications. Further, the security of blockchain itself is a focus in this paper. In particular, we assess the blockchain security from risk analysis to derive comprehensive blockchain security risk categories, analyze the real attacks and bugs against blockchain, and summarize the recently developed security measures on blockchain. Finally, the challenges and research trends are presented to achieve more scalable and securer blockchain systems for the massive deployments.
Sejong Lee, Jaehyeon Kim, Yongseok Kwon, Teasung Kim · 5 authors
BACKGROUND: With the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required. OBJECTIVE: Our goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients' privacy in the EMRs through a medical information exchange process that includes data encryption and access control. METHODS: We propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient's EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework. RESULTS: We performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system's performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption-based data encryption method can effectively protect users' EMRs from forgery and privacy leak threats and provide data integrity. CONCLUSIONS: Blockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.
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.
Blockchain is a type of distributed ledger. It is a chain of blocks. Each block contains a series of transactions. Each transaction is for a value transfer or a smart contract execution. The main purpose of the blockchain system is to achieve consensus on transaction sequence without a controller. The transaction processing capability of the blockchain is influenced by the propagation time of a block in the network -- the shorter the block propagation time, the better the transaction processing capability of the blockchain system, and the easier that system can reach consensus. Ethereum is the second-generation blockchain. It supports Turing complete smart contracts. Although many factors will affect the performance of the Ethereum system, the planned future work of the project is to optimise the transaction/block broadcasting process in the Ethereum peer-to-peer network.
The blockchain identity ecosystem offers the possibility of rejecting the outdated identity system and eliminate the intermediaries. Identity management, through blockchain, can allow individuals to take ownership of their identity by creating a global identity (ID) to serve multiple purposes. For user security and ledger consistency, asymmetric cryptography and distributed consensus algorithms can be implemented. Blockchain technology would be able to save costs and increase efficiency due to its key features such as decentralization, persistence, anonymity and auditability. In addition, the digital identity platform would save citizens' time in accessing or exchanging their personal data and records. Instead of being required to appear physically before the service provider, the user may be provided with a digital ID through his/her personal device, such as a smartphone, through which he/she can share his identity details with the service provider, using distributed ledger technology (DLT).
Blockchain technology, initially developed for cryptocurrency, has shown promise in revolutionizing cybersecurity solutions. This paper explores the potential of blockchain in enhancing security across digital platforms by providing a decentralized, transparent, and tamper-resistant framework for data exchange. Through its distributed ledger system, blockchain can address key cybersecurity challenges, such as data integrity, authentication, access control, and vulnerability management. The paper further evaluates its applications in areas like secure communication, identity management, and fraud detection. By reviewing various case studies and current research, this study presents the advantages, limitations, and future prospects of implementing blockchain in cybersecurity, ultimately suggesting a comprehensive approach to integrating this technology in modern security systems.
Blockchain is a chained data structure that combines data blocks in sequence in chronological order. It has the advantages of decentralization, immutability, distribution and transparency. Blockchain is mainly used in economy and finance, judicial practice, social governance, public welfare and charity, and other fields in China. As a new technology, the risks and challenges brought by blockchain include but are not limited to: algorithm security, convenience for crime, difficulty in determining jurisdiction, and inability to guarantee the right to be forgotten. To prevent blockchain risks requires to establish scientific algorithm rules, improve blockchain legislation, innovate regulatory measures, and establish a blockchain global governance system.
Yassine Himeur, Aya Sayed, Abdullah Alsalemi, Faycal Bensaali · 9 authors
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models’ accuracy and ignore issues related to security and the users’ privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users’ private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research.
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This dissertation aims to discuss the effects by regulation on the cryptoassets ecosystem. Given the underlying technologies, as is the case of Blockchain and Distributed Ledger Technology, it is our conclusion that the technology is under constant evolution, making regulatory intervention difficult as it will naturally will not follow at the same space. However, it is our understanding that the regulation to be carried out, would have to entail a switch in the way the legal system is shaped considering that online reality will overlap as well as find itself in contradiction with the physical world. Notwithstanding, there are several legislative initiatives that have been chained together, in special the advances made by the European Commission which are expected to enter into force in 2024. Under the qualification of cryptoassets made by the European Unition, it is our opinion, that are in contradiction with the nature of it. Finally, we conclude that the Portuguese legal system is equipped with the legal tools to regulate this reality. We conclude that regulation may be the end of the cryptoassets consolidation considering that it is based in beliefs in anarchy that sustain the entire market, without any central power involved.
WAN ATIQAH WAN JAMARUL IMRAN, Mohamed Hisham Yahya, Muhammad Hafiz Ali, MOHD AKBAL QAMAS ABDUL BASIR .
This research studies the factors that affect volatility in cryptocurrency markets. The relationship between information asymmetry and cybercriminal risks are studied against the volatility and return of cryptocurrencies, namely, Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) dan Ripple (XRP). These cryptocurrencies are selected as they are cryptocurrencies that are being traded by Luno, Sinergy and Tokenzie (the exchange companies regulated by the Securities Commissions of Malaysia). 730 observations were collected for each cryptocurrency via the CoinMarketCap website, from 1 January 2019 to 30 December 2020. The ADF test and the Kolmogorov-Smirnov test have been conducted before the analysis of the data. The results show the stationarity and non-normality of the data collected. The EGARCH-GED model is used to analyse the relationship between information asymmetry and volatility. The findings indicate a significant relationship between information asymmetry and volatility in BTC, ETH ad XRP. The Event Study Method (ESM) is used to analyse the effect of cybercriminal risks on returns. The result shows that all four cryptocurrencies show a significant relationship between cybercriminal risks and returns.
Wider coverage and a better solution to a latency reduction in 5G necessitate its combination with multi-access edge computing (MEC) technology. Decentralized deep learning (DDL) such as federated learning and swarm learning as a promising solution to privacy-preserving data processing for millions of smart edge devices, leverages distributed computing of multi-layer neural networks within the networking of local clients, whereas, without disclosing the original local training data. Notably, in industries such as finance and healthcare where sensitive data of transactions and personal medical records is cautiously maintained, DDL can facilitate the collaboration among these institutes to improve the performance of trained models while protecting the data privacy of participating clients. In this survey paper, we demonstrate the technical fundamentals of DDL that benefit many walks of society through decentralized learning. Furthermore, we offer a comprehensive overview of the current state-of-the-art in the field by outlining the challenges of DDL and the most relevant solutions from novel perspectives of communication efficiency and trustworthiness.
Blockchain has become a key technology in a plethora of application domains owing to its decentralized public nature. The cyber-physical systems (CPS) is one of the prominent application domains that leverage blockchain for myriad oper-ations, where the Internet of Things (IoT) is utilized for data collection. Although some of the CPS problems can be solved by simply adopting blockchain for its secure and distributed nature, others require complex considerations for overcoming blockchain-imposed limitations while maintaining the core aspect of CPS. Even though a number of studies focus on either the utilization of block chains for different CPS applications or the blockchain-enabled security of CPS, there is no comprehensive survey including both perspectives together. To fill this gap, we present a comprehensive overview of contemporary advancement in using blockchain for enhancing different CPS operations as well as improving CPS security. To the best of our knowledge, this is the first paper that presents an in-depth review of research on blockchain-enabled CPS operation and security.