We have built a bare-metal testbed in order to perform large-scale, reproducible evaluations of erasure coding algorithms. Our testbed supports at least 1000 Ethereum Swarm peers running on 30 machines. Running experimental evaluation is time-consuming and challenging. Researchers must consider the experimental software's limitations and artifacts. If not controlled, the network behavior may cause inaccurate measurements. This paper shares the lessons learned from a bare-metal evaluation of erasure coding algorithms and how to create a controlled-environment in a cluster consisting of 1000 Ethereum Swarm peers.
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight 'Tangle' based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions.
The spread of blockchain technology is gaining ground worldwide, including in the supply chain and logistics sector. Its proliferation is expected to transform supply chains. Academic research is needed to investigate the reasons for and barriers to adoption. The objective of this study is to explore the blockchain (BC) platform and its inputs as technological solutions. In addition, the application of blockchain technology in managing supply chain (SC) business processes like shipment tracking, authenticity, and identification is also a focus of research. This research was carried out in three ways to explore the issue. Expert interviews were used to develop a research framework for the comparative analysis of BC platforms to find out the benefits and the barriers of blockchain adoption. In association with the diffusion of the technology, a qualitative comparative analysis was applied to benchmark blockchain platform providers. We analysed the blockchain-supply chain market by component, provider, type, and the conditions of usage. As part of this research, the Forbes TOP 50 companies were analysed by business area, country of origin, application area, and benefits in order to see in which area they applied blockchain technology and what improvements they have achieved. The results revealed that blockchain use in supply chains of selected industries has outstanding benefits of transparency, trustworthiness, traceability, and cost efficiencies which give businesses an advantage in terms of implementation costs, technology needs, human resources, legal environments, volatile costs, and security. In the supply chain, Hyperledger Fabric and Ethereum are the most widely used blockchain platforms. For practical implication, the application and benefits of BC in SC were analysed, and the results indicate the traceability, sustainability-related, cost, and time-saving benefits.
The Internet of Things (IoT) has rapidly progressed in recent years and immensely influenced many industries in how they operate. Consequently, IoT technology has improved productivity in many sectors, and smart farming has also hugely benefited from the IoT. Smart farming enables precision agriculture, high crop yield, and the efficient utilization of natural resources to sustain for a longer time. Smart farming includes sensing capabilities, communication technologies to transmit the collected data from the sensors, and data analytics to extract meaningful information from the collected data. These modules will enable farmers to make intelligent decisions and gain profits. However, incorporating new technologies includes inheriting security and privacy consequences if they are not implemented in a secure manner, and smart farming is not an exception. Therefore, security monitoring is an essential component to be implemented for smart farming. In this paper, we propose a cloud-enabled smart-farm security monitoring framework to monitor device status and sensor anomalies effectively and mitigate security attacks using behavioral patterns. Additionally, a blockchain-based smart-contract application was implemented to securely store security-anomaly information and proactively mitigate similar attacks targeting other farms in the community. We implemented the security-monitoring-framework prototype for smart farms using Arduino Sensor Kit, ESP32, AWS cloud, and the smart contract on the Ethereum Rinkeby Test Network and evaluated network latency to monitor and respond to security events. The performance evaluation of the proposed framework showed that our solution could detect security anomalies within real-time processing time and update the other farm nodes to be aware of the situation.
This paper examines and confirms the varying volatility of the relationship between cryptocurrency and currency markets at different time periods, such as when the market encountered multiple risk events including the US–China trade war, COVID-19, and the Russian–Ukraine war. We employ the Diagonal BEKK model and find that the co-volatility spillover effects between the returns of cryptocurrencies and currencies, with the exception of Tether and the U.S. dollar index, evolved significantly. Furthermore, the co-volatility spillover effects between cryptocurrencies and EUR have the largest effects and fluctuations. Large-cap cryptocurrencies (Bitcoin and Ethereum) have greater co-volatility spillover effects between them and currencies. Regarding the ability of cryptocurrencies to act as safe-haven for currencies, we observe that Bitcoin, Ethereum, and Tether served as safe-havens during the US–China trade war, and Bitcoin was a safe-haven during COVID-19. During the 2022 Russian–Ukraine war, Bitcoin and Tether were safe-havens. Interestingly, our findings point out that Bitcoin provides a more consistent safe-haven function for currency markets. Overall, by including multiple global risk events and a comprehensive dataset, the results support our conjecture (and earlier studies) indicating that the capabilities of cryptocurrency are time-varying and related to market status and risk events with different natures.
This study aims to establish the model of the cryptocurrency price trend based on a financial theory using the Long Short-Term Memory (LSTM) networks model with multiple combinations between the window length and the predicting horizons. The Random Walk model is also applied with different parameter settings. The object of this study is the cryptocurrency and medical issues, primarily the Bitcoin and Ethereum and the COVID-19. Quantitative analysis is adopted as the method of this dissertation. The research tool is Python programming language, and the TensorFlow package is employed to model and analyze research topics. The results of this study show the limitations of the LSTM and Random Walk model for price prediction while demonstrating the different characteristics of both models with different parameter settings, providing a balance between the model's accuracy and the model's practicality.
This study investigates the scale-dependent structure of asymmetric volatility effect in six representative cryptocurrencies: Bitcoin, Ethereum, Ripple, Litecoin, Monero, and Dash. By developing the dynamical approach of DFA-based fractal regression analysis, we detect whether the volatility of price changes is positively or negatively related to return shocks at different time scales. We find that the asymmetric volatility phenomenon varies by scale and cryptocurrency, and the structure is time-varying. Contrary to what is typically observed in equity markets, minor currencies show an “inverse” asymmetric volatility effect at relatively large scales, where positive shocks (good news) have a greater impact on volatility than negative shocks (bad news). The consequences are discussed in the context of who is trading in the market and heterogeneity of the investors.
Houpeng Hu, Jiaxiang Ou, Bin Qian, Yi Luo · 7 authors
E-voting allows us to build a democratic business in most Internet of things (IoT) systems. For example, we may vote to choose a proper energy broker in a smart grid system. In this study, we focus on e-voting services in an Internet of energy (IoE) system, which is a new-style smart grid. A practical e-voting in IoE may focus on the properties of fairness, decentralization, eligibility, anonymity, compatibility, verifiability, and coercion resistance. It is difficult to fulfil all these properties simultaneously. Traditional voting schemes often use a public bulletin board or administrator in the voting process, which makes them become centralized. Services that offer e-voting via blockchain can make the voting schemes decentralized. However, many of them ignore the complexity of organizing the data of the transactions, which should be confirmed by the miners. Moreover, to the best of the authors’ knowledge, no works have tested the performance in the blockchain while considering practical use cases and constraints. Concerning all the challenges, we propose a practical anonymous voting scheme for IoE called IoEPAV. The proposed scheme fulfils all the mentioned design goals simultaneously. We tested IoEPAV both in different test networks of the Ethereum blockchain to give an overall evaluation. The practical evaluation can show that the proposed scheme is easy to be integrated into a real system like IoE. We also gave a comparison analysis with the state-of-the-art blockchain-based e-voting. All the results show that IoEPAV is decentralized, verifiable, anonymous, and highly efficient.
The advance of information technology has a growing influence on one of the most popular social trends: online shopping. The rising popularity of online shopping among the general public, as indicated by the growth in the number of online purchasers each year, has prompted business owners to pursue online ventures. The marketplace is intrinsically tied to online buying activity that connects merchants and customers, allowing customers to search for various goods and services from various providers. However, service failures are vulnerable to centralized market systems that emerge frequently. When the company's services to customers fail to satisfy consumer expectations. A breakdown in purchasing and selling essential services, including product delivery and customer support, is referred to as service failure. As a result, not only does this harm confidence, but it may also cause clients to migrate to an alternative marketplace. The marketplace's competitiveness is based on consumer confidence. The decentralized marketplace can address this security concern. A decentralized marketplace is meant to build a system that does not require the confidence of a third party using blockchain technology and smart contracts that can record all transactions clearly and consistently, allowing them to serve as a single point of truth between distrusting entities. The findings largely support the feasibility of Ethereum Smart Contracts to construct a decentralized marketplace. However, there are some places where further study and development are needed.
Abstract In recent decades, the world has witnessed cloud computing as an essential technology that changes the traditional application Development and Operation (DevOps) lifecycle. However, current cloud software DevOps and Service Level Agreement (SLA) management often face challenges of 1) selecting the best fitting service providers, customizing services and planning capacities for large-scale distributed applications; 2) guaranteeing high-quality and trustworthy SLAs among multiple service providers; 3) enhancing the interoperability of cloud services across different providers; and 4) designing effective incentive models among stakeholders. This paper proposes a novel framework called Auction and Witness Enhanced trustworthy SLA for Open, decentralized service MarkEtplaces (AWESOME) to build a trustworthy cloud marketplace and address the above challenges. The proposed framework contains four subsystems: a customizable graphical user interface, an auction-based service selection model, a witness committee management mechanism, and a smart contract factory orchestration. We developed a prototype AWESOME decentralized application (DApp) based on the Ethereum blockchain. Extensive experiments are designed to evaluate the latency and cost of our model. The experimental results demonstrate that our model is economical and feasible.
In this paper, a delegate contract signing solution is proposed to eliminate the potential risk of contract fraud caused by information and interest asymmetry. By utilizing the functional properties of the Ethereum blockchain and smart contracts, a delegate contract signing mechanism is established. By running the mechanism, the delegate contract signing information is received and processed, and the information is broadcast to the blockchain network nodes. By designing the algorithms of "requesting contract signing", "successful contract signing" and "contract fraud dispute resolution", the delegate contract signing is realized. By proposing algorithms and their calling processes, the smart contracts are completed. Finally, the smart contracts based on the solution are tested and verified. The source code of the smart contracts has been published on GitHub.
Ms. Megha Rani R, Roshan R Acharya, Ramkishan, Ranjith K · 5 authors
Travel has been challenging recently since different nations have implemented varied immigration and travel policies. For the time being, immigration officials want proof of each person's immunity to the virus. A vaccine passport serves as evidence that a person has tested negative for or is immune to a particular virus. In terms of COVID-19, those who hold a vaccine passport will be permitted entry into other nations as long as they can provide proof that they have COVID-19 antibodies from prior infections or from full COVID-19 immunizations. To reduce time and effort spent managing data, the vaccination passport system has been digitalized. The process of contact tracing may be facilitated by digitization. The "Blockchain technology" system, which is currently in use, has demonstrated its security and privacy in systems for data exchange among bitcoin users. The Digital Vaccination Passport scheme can use Blockchain technology. The end result would be a decentralized, traceable, transparent, reliable, auditable, secure, and trustworthy solution based on the Ethereum block-chain that would allow tracking of vaccines given and the history of diseases.
Kirtirajsinh Zala, Hiren Kumar Thakkar, Rajendrasinh Jadeja, Neel H. Dholakia · 7 authors
Traditional healthcare services have changed into modern ones in which doctors can diagnose patients from a distance. All stakeholders, including patients, ward boy, life insurance agents, physicians, and others, have easy access to patients' medical records due to cloud computing. The cloud's services are very cost-effective and scalable, and provide various mobile access options for a patient's electronic health records (EHRs). EHR privacy and security are critical concerns despite the many benefits of the cloud. Patient health information is extremely sensitive and important, and sending it over an unencrypted wireless media raises a number of security hazards. This study suggests an innovative and secure access system for cloud-based electronic healthcare services storing patient health records in a third-party cloud service provider. The research considers the remote healthcare requirements for maintaining patient information integrity, confidentiality, and security. There will be fewer attacks on e-healthcare records now that stakeholders will have a safe interface and data on the cloud will not be accessible to them. End-to-end encryption is ensured by using multiple keys generated by the key conclusion function (KCF), and access to cloud services is granted based on a person's identity and the relationship between the parties involved, which protects their personal information that is the methodology used in the proposed scheme. The proposed scheme is best suited for cloud-based e-healthcare services because of its simplicity and robustness. Using different Amazon EC2 hosting options, we examine how well our cloud-based web application service works when the number of requests linearly increases. The performance of our web application service that runs in the cloud is based on how many requests it can handle per second while keeping its response time constant. The proposed secure access scheme for cloud-based web applications was compared to the Ethereum blockchain platform, which uses internet of things (IoT) devices in terms of execution time, throughput, and latency.
The coronavirus, formerly known as COVID-19, has caused massive global disasters. As a precaution, most governments imposed quarantine periods ranging from months to years and postponed significant financial obligations. Furthermore, governments around the world have used cutting-edge technologies to track citizens’ activity. Thousands of sensors were connected to IoT (Internet of Things) devices to monitor the catastrophic eruption with billions of connected devices that use these novel tools and apps, privacy and security issues regarding data transmission and memory space abound. In this study, we suggest a blockchain-based methodology for safeguarding data in the billions of devices and sensors connected over the internet. Various trial secrecy and safety qualities are based on cutting-edge cryptography. To evaluate the proposed model, we recommend using an application of the system, a Raspberry Pi single-board computer in an IoT system, a laptop, a computer, cell phones and the Ethereum smart contract platform. The models ability to ensure safety, effectiveness and a suitable budget is proved by the Gowalla dataset results.
We study the competition between blockchains in a \emph{multi-chain} environment, where a dominant EVM-compatible blockchain (e.g., Ethereum) co-exists with an alternative EVM-compatible (e.g., Avalanche) and an EVM-incompatible (e.g., Algorand) blockchain. While EVM compatibility allows existing Ethereum users and developers to migrate more easily over to the alternative layer-1, EVM incompatibility might allow the firms to build more loyal and ``sticky'' user base, and in turn a more robust ecosystem. As such, the choice to be EVM-compatible is not merely a technological decision, but also an important strategic decision. In this paper, we develop a game theoretic model to study this competitive dynamic, and find that at equilibrium, new entrants/developers tend to adopt the dominant blockchain. To avoid adoption failure, the alternative blockchains have to either (1) directly subsidize the new entrant firms or (2) offer better features, which in practice can take form in lower transaction costs, faster finality, or larger network effects. We find that it is easier for EVM-compatible blockchains to attract users through direct subsidy, while it is more efficient for EVM-incompatible blockchains to attract users through offering better features/products.
Miodrag J. Mihaljević, Lianhai Wang, Shujiang Xu, Milan Todorović
This paper proposes an approach for pool mining in public blockchain systems based on the employment of a recently reported consensus protocol with the puzzle based on a symmetric encryption that provides an energy–space trade-off and reduces energy consumption. The proposed architecture employs a pseudo-symmetric allocation of the resources for the blockchain consensus protocol and provides protection against certain malicious actions of the pool members, as well as a miner’s opportunity for selecting the resources required for participation in the consensus protocol. Given that the considered consensus protocol employs two resources, the proposed architecture uses this two-dimensional nature to provide resistance against block withholding and selfish mining attacks, as well as a reduction in energy spending as a trade-off with the employment of certain memory resources. The high resistance of the proposed pool mining approach against the considered attacks appears to be a consequence of the success probability of the pool in comparison with the success probability of malicious miners. Assuming appropriate selection of the puzzle hardness, the probability that malicious miners can solve the puzzle without the support of the pool manager can be arbitrarily small. Implementation of the proposed approach on a modified Ethereum platform and experimental evaluation issues have also been reported. The conceptual novelty of the proposed pool mining approach is the following: Instead of separation of the blockchain consensus protocol and control of pool miners honest work, this paper proposes an approach where honest work of miners and pool managers is provided by a dedicated application of the considered consensus protocol. Advantages of the proposal in comparison with the previously reported ones include the following: (i) high resistance against block withholding and selfish mining attacks without an additional security procedure; (ii) reduction in the energy required, and at the same time preservationthe security of the consensus protocol; (iii) flexibility of the pool miners regarding selection of the resources that should be employed providing a trade-off between required energy and memory resources. The proposed architecture was implemented employing a dedicated modification of the Ethereum platform and the performed experiments confirmed the feasibility and effectiveness of the proposal.
Threats towards information systems have continued to increase and become more sophisticated, making security approaches a necessity for all types of organizations to ensure their protection. To implement an appropriate computer security policy, it is necessary to efficiently exploit the data that has become a valuable asset for these security systems, provided it is well used, controlled and monitored.In this paper, we focus on developing a decentralized solution based on Blockchain technology and IPFS (InterPlanetary File System) that can maintain and ensure the integrity of log files and sensitive information. The obtained results are promising, we obtained a distributed ledger of all log file transactions in a chronological sequence, which was shared among all Ethereum participants, allowing us to verify the log files' integrity, validity, and auditability throughout their life cycle.
Theo Diamandis, Alex Evans, Tarun Chitra, Guillermo Angeris
Public blockchains implement a fee mechanism to allocate scarce computational resources across competing transactions. Most existing fee market designs utilize a joint, fungible unit of account (e.g., gas in Ethereum) to price otherwise non-fungible resources such as bandwidth, computation, and storage, by hardcoding their relative prices. Fixing the relative price of each resource in this way inhibits granular price discovery, limiting scalability and opening up the possibility of denial-of-service attacks. As a result, many prominent networks such as Ethereum and Solana have proposed multi-dimensional fee markets. In this paper, we provide a principled way to design fee markets that efficiently price multiple non-fungible resources. Starting from a loss function specified by the network designer, we show how to compute dynamic prices that align the network's incentives (to minimize the loss) with those of the users and miners (to maximize their welfare), even as demand for these resources changes. Our pricing mechanism follows from a natural decomposition of the network designer's problem into two parts that are related to each other via the resource prices. These results can be used to efficiently set fees in order to improve network performance.
Limited scalability and transaction costs are, among others, some of the critical issues that hamper a wider adoption of distributed ledger technologies (DLT). That is particularly true for the Ethereum blockchain, which, so far, has been the ecosystem with the highest adoption rate. Quite a few solutions, especially on the Ethereum side of things, have been attempted in the last few years. Most of them adopt the approach to offload transactions from the blockchain mainnet, a.k.a. Level 1 (L1), to a separate network. Such systems are collectively known as Level 2 (L2) systems. While mitigating the scalability issue, the adoption of L2 introduces additional drawbacks: users have to trust that the L2 system has correctly performed transactions or, conversely, high computational power is required to prove transactions correctness. In addition, significant technical knowledge is needed to set up and manage such an L2 system. To tackle such limitations, we propose 1DLT: a novel system that enables rapid and trustless deployment of an Ethereum Virtual Machine based blockchain that overcomes those drawbacks.
Khizar Hameed, Ali Raza, Saurabh Garg, Muhammad Bilal Amin
An authorisation has been recognised as an important security measure for preventing unauthorised access to critical resources, such as devices and data, within the Internet of Things (IoT) networks. Existing authorisation methods for the IoT network are based on traditional access control models, which have several drawbacks, including architecture centralisation, policy tampering, access rights validation, malicious third-party policy assignment and control, and network-related overheads. The increasing trend of integrating Blockchain technology with IoT networks demonstrates its importance and potential to address the shortcomings of traditional IoT network authorisation mechanisms. This paper proposes a decentralised, secure, dynamic, and flexible authorisation scheme for IoT networks based on attribute-based access control (ABAC) fine-grained policies stored on a distributed immutable ledger. We design a Blockchain-based ABAC policy management framework divided into Attribute Management Authority (AMA) and Policy Management Authority (PMA) frameworks that use smart contract features to initialise, store, and manage attributes and policies on the Blockchain. To achieve flexibility and dynamicity in the authorisation process, we capture and utilise the environmental-related attributes in conjunction with the subject and object attributes of the ABAC model to define the policies. Furthermore, we designed the Blockchain-based Access Management Framework (AMF) to manage user requests to access IoT devices while maintaining the privacy and auditability of user requests and assigned policies. We implemented a prototype of our proposed scheme and executed it on the local Ethereum Blockchain. Finally, we demonstrated the applicability and flexibility of our proposed scheme for an IoT-based smart home scenario, taking into account deployment, execution and financial costs.
Fatih Ecer, Adem Böyükaslan, Sarfaraz Hashemkhani Zolfani
Blockchain technologies, which form the basis of Industry 4.0, paved the way for cryptocurrencies to emerge as technological innovation in the technology age. Recently, investors worldwide have been interested in cryptocurrencies with increasing acceleration due to high earning expectations though they have no backing and intrinsic value. As such, this paper seeks to identify the most proper cryptocurrencies from an investment standpoint in our technological era. Fifteen well-known cryptocurrencies with the highest market capitalization are evaluated as per sixteen factors. An intuitionistic fuzzy set-driven methodology incorporating Evaluation Based on Distance from Average Solution (EDAS), Multi-Attributive Ideal Real Comparative Analysis (MAIRCA, and Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS), which is the study’s prominent novelty, has been applied to provide a strong group decision vehicle for cryptocurrency selection. Notwithstanding, although the results obtained with the three approaches are highly consistent, investors would not like to doubt the instrument they will invest in. The Borda count is then applied to obtain a compromise for the rankings obtained from each approach. As per our findings, Ethereum, Tether, and Bitcoin are the most suitable cryptocurrencies, whereas reliable software, ease of inclusion in the wallet, and stability are the foremost factors to consider when investing in cryptocurrencies. The findings are further discussed in detail from a financial perspective. The proposed approach could be employed to select different investment instruments in future studies.
Ethereum, a well-known blockchain’s most famous implementation builds and deploys a decentralized application where users can transact with cryptocurrency using smart contracts. The latest technological developments in cryptocurrencies and the benefits associated with them have been hidden by a number of illegal activities on the network. Like bribery, phishing scam, money laundering and fraud etc. The ‘Pseudoanonymous’ nature of the participants in Ethereum blockchain network leads to cause difficulty in detecting illicit behavior of the users. Anomalies must be detected and resolved quickly to ensure participant trust in the largest blockchain platforms. There is a lot of work on detailed analysis of Ethereum transactions in terms of how well they work, but this research is the first to the best of my knowledge to detect anomalies in Ethereum transaction records. To achieve our goal, we have extracted more comprehensive feature of Ethereum transaction data to get rid of the shortcomings of existing work. We have used SMOTE technique to deal with highly imbalanced dataset and implemented five supervised-machine-learning model, Logistic-Regression, KNN, Decision-tree, Random-Forest and SVC classifier to access and compare the best performer among them. Random Forest Outperforms with accuracy of 98%. We evaluated the accuracy, precision, and F-value of each method and backed them up with experimental results.
Searchable encryption enables users to enjoy search services while protecting the security and privacy of their outsourced data. Blockchain-enabled searchable encryption delivers the computing processes that are executed on the server to the decentralized and transparent blockchain system, which eliminates the potential threat of malicious servers invading data. Recently, although some of the blockchain-enabled searchable encryption schemes realized that users can search freely and verify search results, unfortunately, these schemes were inefficient and costly. Motivated by this, we proposed an improved scheme that supports fine-grained access control and flexible searchable encryption. In our framework, the data owner uploads ciphertext documents and symmetric keys to cloud database and optional KMS, respectively, and manipulates the access control process and searchable encryption process through smart contracts. Finally, the experimental comparison conducted on a private Ethereum network proved the superiority of our scheme.
The core of many cryptocurrencies is the decentralised validation network operating on proof-of-work technology. In these systems, validation is done by so-called miners who can digitally sign blocks once they solve a computationally-hard problem. Conventional wisdom generally considers this protocol as secure and stable as miners are incentivised to follow the behaviour of the majority. However, whether some strategic mining behaviours occur in practice is still a major concern. In this paper we target this question by focusing on a security threat: a selfish mining attack in which malicious miners deviate from protocol by not immediately revealing their newly mined blocks. We propose a statistical test to analyse each miner's behaviour in five popular cryptocurrencies: Bitcoin, Litecoin, Monacoin, Ethereum and Bitcoin Cash. Our method is based on the realisation that selfish mining behaviour will cause identifiable anomalies in the statistics of miner's successive blocks discovery. Secondly, we apply heuristics-based address clustering to improve the detectability of this kind of behaviour. We find a marked presence of abnormal miners in Monacoin and Bitcoin Cash, and, to a lesser extent, in Ethereum. Finally, we extend our method to detect coordinated selfish mining attacks, finding mining cartels in Monacoin where miners might secretly share information about newly mined blocks in advance. Our analysis contributes to the research on security in cryptocurrency systems by providing the first empirical evidence that the aforementioned strategic mining behaviours do take place in practice.