Purpose This paper aims to identify and quantify directional predictability between returns and volume in major cryptocurrencies markets. Design/methodology/approach The empirical analysis relies on the cross-quantilogram approach that allows one to assess the temporal (lag-lead) association between two stationary time series at different parts of their joint distribution. The data are daily prices and trading volumes from four markets (Bitcoin, Ethereum, Ripple and Litecoin). Findings Extreme returns either positive or negative tend to lead high volume levels. Low levels of trading activity have in general no information content about future returns; high levels, however, tend to precede extreme positive returns. Originality/value This is the first work that uses the cross-quantilogram approach to assess the temporal association between returns and volume in cryptocurrencies markets. The findings provide new insights about the informational efficiency of these markets and the traders’ strategies.
Andrea Lisi, Andrea De Salve, Paolo Mori, Laura Ricci · 5 authors
Recommender Systems (RSs) are becoming increasingly popular in the last years. They collect reviews concerning several types of items (e.g., shops, professionals, services, songs or videos) in order to rank them according to a given criterion, and to suggest the most relevant ones to their users. However, most of the currently used RSs exhibit two main drawbacks: they are based on a centralized control model and they do not provide reward mechanisms to encourage the participation of users. To deal with these challenges, the architectures of current RSs could be enhanced through blockchain technology, thus providing novel solutions to decentralize them. As a matter of fact, the blockchain technology could be successfully adopted in this context because smart contracts would allow the decentralization of system control, while cryptocurrency and tokens could be used to implement the reward mechanism. In the light of the above considerations, this manuscript presents a decentralized rating framework aimed to support the users of RSs based on blockchain technology, providing a token-based reward mechanism that remunerates users submitting their reviews to incentivize their participation. Moreover, the proposed system provides a flexible strategy to rank items, allowing users to choose among different functions to combine reviews to obtain item ranking. The performance and the cost of using the proposed system have been evaluated on the Ropsten Ethereum test network. For instance, our experiments have shown that the median time required to store a batch of 35 ratings is about 47 s, while the average time required to obtain the score of an item having 6000 ratings is less than 2.5 s.
Marco Ortu, Nicola Uras, Claudio Conversano, Giuseppe Destefanis · 5 authors
This work aims to analyse the predictability of price movements of cryptocurrencies on both hourly and daily data observed from January 2017 to January 2021, using deep learning algorithms. For our experiments, we used three sets of features: technical, trading and social media indicators, considering a restricted model of only technical indicators and an unrestricted model with technical, trading and social media indicators. We verified whether the consideration of trading and social media indicators, along with the classic technical variables (such as price's returns), leads to a significative improvement in the prediction of cryptocurrencies price's changes. We conducted the study on the two highest cryptocurrencies in volume and value (at the time of the study): Bitcoin and Ethereum. We implemented four different machine learning algorithms typically used in time-series classification problems: Multi Layers Perceptron (MLP), Convolutional Neural Network (CNN), Long Short Term Memory (LSTM) neural network and Attention Long Short Term Memory (ALSTM). We devised the experiments using the advanced bootstrap technique to consider the variance problem on test samples, which allowed us to evaluate a more reliable estimate of the model's performance. Furthermore, the Grid Search technique was used to find the best hyperparameters values for each implemented algorithm. The study shows that, based on the hourly frequency results, the unrestricted model outperforms the restricted one. The addition of the trading indicators to the classic technical indicators improves the accuracy of Bitcoin and Ethereum price's changes prediction, with an increase of accuracy from a range of 51-55% for the restricted model, to 67-84% for the unrestricted model.
Marco Ortu, Nicola Uras, Claudio Conversano, Giuseppe Destefanis · 5 authors
This work aims to analyse the predictability of price movements of\ncryptocurrencies on both hourly and daily data observed from January 2017 to\nJanuary 2021, using deep learning algorithms. For our experiments, we used\nthree sets of features: technical, trading and social media indicators,\nconsidering a restricted model of only technical indicators and an unrestricted\nmodel with technical, trading and social media indicators. We verified whether\nthe consideration of trading and social media indicators, along with the\nclassic technical variables (such as price's returns), leads to a significative\nimprovement in the prediction of cryptocurrencies price's changes. We conducted\nthe study on the two highest cryptocurrencies in volume and value (at the time\nof the study): Bitcoin and Ethereum. We implemented four different machine\nlearning algorithms typically used in time-series classification problems:\nMulti Layers Perceptron (MLP), Convolutional Neural Network (CNN), Long Short\nTerm Memory (LSTM) neural network and Attention Long Short Term Memory (ALSTM).\nWe devised the experiments using the advanced bootstrap technique to consider\nthe variance problem on test samples, which allowed us to evaluate a more\nreliable estimate of the model's performance. Furthermore, the Grid Search\ntechnique was used to find the best hyperparameters values for each implemented\nalgorithm. The study shows that, based on the hourly frequency results, the\nunrestricted model outperforms the restricted one. The addition of the trading\nindicators to the classic technical indicators improves the accuracy of Bitcoin\nand Ethereum price's changes prediction, with an increase of accuracy from a\nrange of 51-55% for the restricted model, to 67-84% for the unrestricted model.\n
Célio Márcio Soares Ferreira, Charles Tim Batista Garrocho, Ricardo Oliveira, Jorge Sá Silva · 5 authors
The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these applications being Smart Cities (SC). IoT devices in new network paradigms, such as Edge Computing and Fog Computing, will collect data from urban environments, providing real-time management information. One of these challenges is ensuring that the data sent from Edge Computing are reliable. Blockchain has been a technology that has gained the spotlight in recent years, due to its robust security in fintech and cryptocurrencies. Its strong encryption and distributed and decentralized network make it potential for this challenge. Using Blockchain with IoT makes it possible for SC applications to have security information distributed, which makes it possible to shield against Distributed Denial of Service (DDOS). IoT devices in an SC can have a long life, which increases the chance of having security holes caused by outdated firmware. Adding a layer of identification and verification of attributes and signature of messages coming from IoT devices by Smart Contracts can bring confidence in the content. SC Apps that extract data from legacy and outdated appliances, installed in inaccessible, unknown, and often untrusted urban environments can benefit from this work. Our work's main contribution is the development of API Gateways to be used in IoT devices and network gateway to sign, identify, and authorize messages. For this, keys and essential characteristics of the devices previously registered in Blockchain are used. We will discuss the importance of this implementation while considering the SC and present a testbed that is composed of Blockchain Ethereum and real IoT devices. We analyze the transfer time, memory, and CPU impacts during the sending and processing of these messages. The messages are signed, identified, and validated by our API Gateways and only then collected for an IoT data management application.
Dataset retrieved with an Ethereum client, and used by the code hosted here for this paper published in the Proceedings of the Web Conference 2021 (WWW ’21) Abstract: Cryptoassets such as cryptocurrencies and tokens are increasingly traded on decentralized exchanges. The advantage for users is that the funds are not in custody of a centralized external entity. However, these exchanges are prone to manipulative behavior. In this paper, we illustrate how wash trading activity can be identified on two of the first popular limit order book-based decentralized exchanges on the Ethereum blockchain, IDEX and EtherDelta. We identify a lower bound of accounts and trading structures that meet the legal definitions of wash trading, discovering that they are responsible for a wash trading volume in equivalent of 159 million U.S. Dollars. While self-trades and two-account structures are predominant, complex forms also occur. We quantify these activities, finding that on both exchanges, more than 30% of all traded tokens have been subject to wash trading activity. On EtherDelta, 10% of the tokens have almost exclusively been wash traded. All data is made available for future research. Our findings underpin the need for countermeasures that are applicable in decentralized systems.
Mohammad Madine, Khaled Salah, Raja Jayaraman, Yousof Al-Hammadi · 6 authors
Blockchain technology has the potential to revolutionize industries by offering decentralized, transparent, data provenance, auditable, reliable, and trustworthy features. However, cross-chain interoperability is one of the crucial challenges preventing widespread adoption of blockchain applications. Cross-chain interoperability represents the ability for one blockchain network to interact and share data with another blockchain network. Contemporary cross-chain interoperability solutions are centralized and require re-engineering of the core blockchain stack to enable inter-communication and data sharing among heterogeneous blockchain networks. In this paper, we propose an application-based cross-chain interoperability solution that allows blockchain networks of any architecture type and industrial focus to inter-communicate, share data, and make requests. Our solution utilizes the decentralized applications as a distributed translation layer that is capable of communicating and understanding multiple blockchain networks, thereby delegating requests and parameters among them. The architecture uses incentivized verifier nodes that maintain the integrity of shared data facilitating them to be readable by the entities of their network. We define and describe the roles and requirements of major entities of inter-operating blockchain networks in the context of healthcare. We present a detailed explanation of the sequence of interactions needed to share an Electronic Medical Record (EMR) document from one blockchain network to another along with the required algorithms. We implement the proposed solution with Ethereum-based smart contracts for two hospitals and also present cost and security analysis for the cross-chain interoperability solution. We make our smart contracts code and testing scripts publicly available.
A. F. M. Suaib Akhter, Mohiuddin Ahmed, A. F. M. Shahen Shah, Adnan Anwar · 6 authors
The efficiency of cooperative communication protocols to increase the reliability and range of transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification and communication security are required to be ensured. Though it is difficult to maintain strong network connections between vehicles because of there high mobility, with the help of cooperative communication, it is possible to increase the communication efficiency, minimise delay, packet loss, and Packet Dropping Rate (PDR). However, cooperating with unknown or unauthorized vehicles could result in information theft, privacy leakage, vulnerable to different security attacks, etc. In this paper, a blockchain based secure and privacy preserving authentication protocol is proposed for the Internet of Vehicles (IoV). Blockchain is utilized to store and manage the authentication information in a distributed and decentralized environment and developed on the Ethereum platform that uses a digital signature algorithm to ensure confidentiality, non-repudiation, integrity, and preserving the privacy of the IoVs. For optimized communication, transmitted services are categorized into emergency and optional services. Similarly, to optimize the performance of the authentication process, IoVs are categorized as emergency and general IoVs. The proposed cooperative protocol is validated by numerical analyses which show that the protocol successfully increases the system throughput and decreases PDR and delay. On the other hand, the authentication protocol requires minimum storage as well as generates low computational overhead that is suitable for the IoVs with limited computer resources.
Carlos Melo, Jamilson Dantas, Paulo Pereira, Paulo Maciel
Blockchain and Cloud Computing are two of the main topics related to the distributed computing paradigm, and in the last decade, they have seen exponential growth in their adoption. Cloud computing has long been established as the main mechanism to test, develop, and deliver new applications and services in a distributed manner across the World Wide Web. Large data centers host many services and store petabytes of user data. Infrastructure and services owners rule the access to data and may even be able to change contents and attest to its veracity. Blockchain is a step towards a future where the user's data are considered safer, besides being public. Advances in blockchain-based technologies, now, support service provisioning over permissioned and private infrastructures. Therefore, organizations or groups of individuals may share information, service even if they do not trust each other, besides supporting infrastructure management tasks. This paper presents and evaluates models for assessing the availability and capacity-oriented availability of cloud computing infrastructures. It aims at running Blockchain's distributed applications based on the Ethereum blockchain platform and the required expenses to perform service delivery in public and private infrastructures. Most of the obtained results also apply to other blockchains based platforms.
Peer-to-peer (p2p) content delivery is promising to reduce the cost of traditional CDNs and complement the decentralized storage networks such as Filecoin. However, reliable p2p delivery requires proper enforcement of delivery fairness, i.e., the deliverers should be rewarded according to their in-time delivery. Unfortunately, most existing studies on delivery fairness are based on non-cooperative game-theoretic assumptions that are arguably unrealistic in the ad-hoc p2p setting. We for the first time put forth the expressive yet still minimalist securities for p2p content delivery, and give two efficient solutions FairDownload and FairStream via the blockchain for p2p downloading and p2p streaming scenarios, respectively. Our designs not only guarantee delivery fairness to ensure deliverers be paid (nearly) proportional to his in-time delivery, but also ensure the content consumers and content providers to be fairly treated. The fairness of each party can be guaranteed when the other two parties collude to arbitrarily misbehave. Moreover, the systems are efficient in the sense of attaining asymptotically optimal on-chain costs and optimal deliverer communication. We implement the protocols to build the prototype systems atop the Ethereum Ropsten network. Extensive experiments done in LAN and WAN settings showcase their high practicality.
With the rapid development and widespread application of crowdsourcing, the limitations of traditional systems are gradually exposed. First, traditional systems fail to protect the privacy of task requesters and workers. They typically rely on a centralized server to aggregate the task content and workers' interests, while these data contain sensitive information. Second, crowdsourcing resources in each system are isolated. The tasks in one system cannot reach potential workers in other systems. Thus, there is a great need to build a new privacy-preserving and federated crowdsourcing system. However, the existing privacy-preserving solutions rely on a trusted third party to perform key management, which is not applicable in a federated setting. To this end, we propose the first proxy-free privacy-preserving and federated crowdsourcing system. It interconnects the existing crowdsourcing systems and can perform encrypted task matching across various systems without relying on a trusted third-party authority. Our main idea is to achieve federated crowdsourcing by moving secure task matching to the trusted smart contract. To get rid of the dependence on the trusted authority, we combine the rewritable deterministic hashing technique with searchable encryption schemes to achieve secure on-chain task-matching authorization. Moreover, we utilize the puncturable encryption technique to implement secure authorization revocation. We formally analyze the security of our design and implement a prototype on Ethereum. Evaluation results demonstrate that our design is secure and efficient for blockchain-based crowdsourcing.
Popular blockchains such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Serial execution of smart contract transactions/atomic-units (AUs) fails to harness the multiprocessing power offered by the prevalence of multi-core processors. By adding concurrency to the execution of AUs, we can achieve better efficiency and higher throughput. In this paper, we develop a concurrent miner that proposes a block by executing the AUs concurrently using optimistic Software Transactional Memory systems (STMs). It captures the independent AUs in a concurrent bin and dependent AUs in the block graph (BG) efficiently. Later, we propose a concurrent validator that re-executes the same AUs concurrently and deterministically using a concurrent bin followed by a BG given by the miner to verify the proposed block. We rigorously prove the correctness of concurrent execution of AUs and achieve significant performance gain over the state-of-the-art.
To support effective supply chain management (SCM) is a challenging issue for healthcare sectors. In healthcare, the requirements of blood to be fulfilled on demands are always directly or indirectly connected to its supply chain. For that, an effective blood supply chain system is required in which blood relevant information will be traceable at each stage of the blood supply (e.g., from donor to blood recipient), with trust and safety in testing, storage, and distribution phases and to keep the privacy of each donor. This study uses a Blockchain Ethereum platform as a solution to leverage traceability in the blood donation supply chain (BDSC). Blockchain is a highly efficient, decentralized, and peer-to-peer distributed technology deploys to provide end-to-end traceability, safety, immutability, and security in the BDSC ecosystem. As a part of this study, a role-based smart contract solution is used to define the access per each role, which therefore assists to ensure traceability and security of information in the BDSC ecosystem.
Mallikarjun Reddy Dorsala, V. N. Sastry, Chapram Sudhakar
With the advent of mobile crowdsensing, the mobile devices equipped with a variety of sensors (such as accelerometer, gyroscope, microphone etc.) are used to collect sensory data. A data aggregator processes the collected sensor data to deliver various services such as traffic management, health care and environmental monitoring. To ensure the privacy of the data, privacy-preserving aggregation (PPA) has attracted much attention since it can find aggregated statistics on the encrypted data. In this paper, we extend the existing PPA schemes in two directions: (1) Aggregator unforgeability – The aggregator performs the aggregation operation correctly. Although there are some schemes which consider aggregator unforgeability, they rely on cryptographic techniques. (2) Fair payments – The data owners receive the payments for their data contribution if and only if the aggregator receives the data. Contrary to existing works, we achieve the aggregator unforgeability and fair payments by modeling the aggregator as a smart contract running on a public Blockchain network. We design two PPA schemes FairNaivePPA and FairPPA for secure aggregation of MCS data with fair payments. We show the financial and transactional cost analysis of proposed contracts by implementing them in solidity and running them on Ethereum Blockchain.
Fátima Leal, Adriana E. Chis, Horacio González–Vélez
Multi-service networks aim to efficiently supply distinct goods within the same infrastructure by relying on a (typically centralised) authority to manage and coordinate their differential delivery at specific prices. In turn, final customers constantly seek to lower costs whilst maximising quality and reliability. This paper proposes a decentralised business model for multi-service networks using Ethereum blockchain features – gas, transactions, and smart contracts – to execute multiple services at different prices. By employing the Ethereum cryptocurrency token, Ether, to quantify the quality of service and reliability of distinct private Ethereum networks, our model concurrently processes streams of services at different gas prices while differentially delivering reliability and service quality. This multi-service business model has been extensively tested on five concurrent Ethereum networks with various combinations of gas prices, miners, and regular nodes using a Proof of Authority consensus algorithm and throughput as the evaluation metric. It has exhibited linear scalability, providing increased throughput in high-quality Ethereum networks, i.e., composed of more validator nodes. The results also indicate that different mining prices do not impact the network performance, but networks with more miners had limited scalability and an increased level of trustworthiness and reliability.
Gianna Figà‐Talamanca, Sergio M. Focardi, Marco Patacca
Abstract In this paper, we apply dynamic factor analysis to model the joint behaviour of Bitcoin, Ethereum, Litecoin and Monero, as a representative basket of the cryptocurrencies asset class. The empirical results suggest that the basket price is suitably described by a model with two dynamic factors. More precisely, we detect one integrated and one stationary factor until the end of August 2019 and two integrated factors afterwards. Based on this evidence, we define a multiple long-short trading strategy which proves profitable when the second factor is stationary.
Raaj Anand Mishra, Anshuman Kalla, An Braeken, Madhusanka Liyanage
Sharing of students’ credentials is a necessary and integral process of an education ecosystem that comprises various stakeholders like students, schools, companies, professors and the governmental authorities. As of today, all these stakeholders have to put-in an enormous amount of efforts to ensure the authenticity and privacy of students’ credentials. Despite these efforts, the process of sharing students’ credentials is complex, error-prone and not completely secure. Our aim is to leverage blockchain technology to mitigate the existing security-related issues concerning the sharing of students’ credentials. Thus, the paper proposes a tamper-proof, immutable, authentic, non-repudiable, privacy protected and easy to share blockchain-based architecture for secured sharing of students’ credentials. To increase the scalability, the proposed system uses a secure off-chain storage mechanism. The performance and viability of the proposed architecture is analyzed by using an Ethereum based prototypical implementation. The test results imply that requests can be executed within few seconds (without block-time) and the system has stability to process up to 1000 simultaneous requests.
Asymmetric relationship between price and volatility is a prominent feature of the financial market time series. This paper explores the price–volatility nexus in cryptocurrency markets and investigates the presence of asymmetric volatility effect between uptrend (bull) and downtrend (bear) regimes. The conventional GARCH-class models have shown that in cryptocurrency markets, asymmetric reactions of volatility to returns differ from those of other traditional financial assets. We address this issue from a viewpoint of fractal analysis, which can cover the nonlinear interactions and the self-similarity properties widely acknowledged in the field of econophysics. The asymmetric cross-correlations between price and volatility for Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC) during the period from June 1, 2016 to December 28, 2020 are investigated using the MF-ADCCA method and quantified via the asymmetric DCCA coefficient. The approaches take into account the nonlinearity and asymmetric multifractal scaling properties, providing new insights in investigating the relationships in a dynamical way. We find that cross-correlations are stronger in downtrend markets than in uptrend markets for maturing BTC and ETH. In contrast, for XRP and LTC, inverted reactions are present where cross-correlations are stronger in uptrend markets.
Ahmed Abdullah A. Shareef, Pravin Yannawar, Zeyad A. T. Ahmed, Ali Mansour Al-madani
Recently, blockchain, deep learning, and computer vision are considered the most fundamental technologies in the world. The researchers have been paying much attention to use them. The centralized database system's problem has low security because it must be transferred through a trusted third party, while the data transmitted might be hacked. However, blockchain provides a distributed database that makes the network secure, flexible, and capable of supporting real-time services. This article proposes a blockchain-based object detection model. The blockchain system makes files secure using the Interplanetary Files System (IPFS) that receives our files, stores them on the decentralized application, and sends the hash to Ethereum to be stored. A YOLOv3 object detection model receives our encrypted data as a hash value and detects objects from images that consist of a huge dataset of different objects.
With the rapid growth in the sector of information technology and easy access to cheap and advanced office instruments in the market, the faking of important documents has become a matter of concern nowadays. Therefore, the need for verification and authentication practices of various important documents in the form of banking documents, government documents, transaction documents, educational certificates etc is also increasing. However, various challenging and tedious processes have made document verification very complex and time-consuming which motivated us to conduct this research. In this paper, we present a decentralized web application for digital document verification using Ethereum blockchain-based technology in P2P cloud storage to enhance the verification process by making it more open, transparent, and auditable. The proposed model includes several methods such as public/private key cryptography, online storage security, digital signatures, hash, peer-to-peer networks and proof of work which has made the verification of any uploaded documents for any organization or authority faster and convenient with just a click. Furthermore, respective hash values are also assigned to each individual document. Our proposed model successfully meets up all the criteria for a digital document verification system by alleviating the gaps and difficulties in the traditional methods in document verification.
Blockchain Technology Applications and Security
Cloud Data Security Solutions
Advanced Steganography and Watermarking Techniques
The technology Block-chain is most emerging and widely used in almost all the applications like supply chain management systems, healthcare, banking industries, business, IT sectors, government organizations, agriculture etc. The food products are more sensitive, and it is very hard to trace the origin, buyers, sellers, farmers with the existing centralized method. The usage of Block-chain technology is proposed and experimented in this work along with the features of decentralization, increased security, immutability, and tamper proof for supply chains. The proposed work uses the smart contract on Ethereum for food supply chain management systems, which avoids falsifying information, corrupting database, external attacks. The analysis of food supply chains is shown in the experimental results.
In today's digital era, data is most important in every phase of work. The storage and processing on data with security is the need of each and every application field. Data need to be tamper resistant due to possibility of alteration. Data can be represented and stored in heterogeneous format. There are chances of attack on information which is vital for particular organization. With rapid increase in cyber crime, attackers behave maliciously to alter those data. But it is having great impact on forensic evidences which is required for provenance. Therefore, it is required to maintain the reliability and provenance of digital evidences as it travels through various stages during forensic investigation. In this approach, there is a forensic chain in which generated report passes through various levels or intermediaries such as pathology laboratory, doctor, police department etc. To build the transparent system with immutability of forensic evidences, blockchain technology is more suitable. Blockchain technology provides the transfer of assets or evidence reports in transparent environment without central authority. In this paper blockchain based secure system for forensic evidences is proposed. The proposed system is implemented on Ethereum platform. The tampering of forensic evidence can be easily traced at any stage by anyone in the forensic chain. The security enhancement of forensic evidences is achieved through implementation on Ethereum platform with high integrity, traceability and immutability.