Blockchain-based voting, including liquid voting, has been extensively studied in recent years. However, it remains challenging to implement liquid voting on blockchain using Ethereum smart contract. The challenge comes from the gas limit, which is that the number of instructions for processing a ballot cannot exceed a certain amount. This restricts the application scenario with respect to algorithms whose time complexity is linear to the number of voters, i.e., O(n). As the blockchain technology can well share and reuse the resources, we study a model of liquid voting on blockchain and propose a fast algorithm, named Flash, to eliminate the restriction. The key idea behind our algorithm is to shift some on-chain process to off-chain. In detail, we first construct a Merkle tree off-chain which contains all voters' properties. Second, we use Merkle proof and interval tree to process each ballot with O(log n) on-chain time complexity. Theoretically, the algorithm can support up to 21000 voters with respect to the current gas limit on Ethereum. Experimentally, the result implies that the consumed gas fee remains at a very low level when the number of voters increases. This means our algorithm makes liquid voting on blockchain practical even for massive voters.
Deep learning has achieved the high-accuracy of state-of-the-art algorithms in long-standing AI tasks. Due to the obvious privacy issues of deep learning, Google proposes Federal Deep Learning (FDL), in which distributed participants only upload local gradients and and a centralized server updates parameters based on the collected gradients. But few users are willing to participate in federated learning due to the lack of contribution evaluation and reward mechanisms. So a decentralized federated deep learning, called DFDL, has been proposed by introducing blockchain to form an effective incentive mechanism for participants. However, DFDL still faces serious privacy issues as blockchain does not guarantee the privacy of training data and model. In this paper, in order to address the aforementioned issues, we propose a new Privacy-preserving DFDL scheme, called PDFDL. With PDFDL, parties can securely learn a global model with their local gradients in the assistance of blockchain, and the parties’ sensitive data and the global model are well protected. Specifically, with a secure multi-party aggregation computing, all local gradients are encrypted by their owners before being sent to the smart contract, and can be directly aggregated without decryption. Detailed security analysis shows that PDFDL can resist various known security threats. Moreover, we give an implementation prototype by integrating deep learning module with a Blockchain development platform (Ethereum V1.6.4). We demonstrate the encryption performance and the training accuracy of our PDFDL on benchmark datasets.
Millions of students complete their education each year and go on to do higher studies or a corporate job. In this case student credentials are verified through a lengthy document verification process. This results in significant overhead as documents are transferred between institutions for verification. There is a need for an automated credential verification system which can reduce the time required for the document verification process. Blockchain Technology can be used to reduce overhead and reduce the time taken for document verification from days to mere seconds. In this work, an attempt has been made to develop a Blockchain-based verification system for academic certificates. With the advent of public Blockchain like Ethereum, DApps (Decentralized Applications) and Smart contracts, scalable and cost effective solutions can be implemented to reduce overhead and make document verification a seamless process. The proposed solution consists of a web app which will have a front-end for registering and requesting verification, along with a backend which will have two modules: An OCR module to extract details from certificates and a Blockchain module to send and verify data stored in the Blockchain.
Safe-haven assets conserve their value or grow against another asset or portfolioduring market turmoil. Indonesian stock market, represented by the Jakarta composite index (JKSE), plunged in price because of COVID-19, pushing investors to look for safe-havens. The cryptocurrency began to be perceived as a store of value as indicated by the transaction volume increase; hence it was expected to be a safe haven asset. However, cryptocurrency’s high price volatility cast doubts on its store of value effectiveness, prompting inspection for its safe haven property as well. This research aimed to predict the assets' risk and return plus investigate whether cryptocurrency is safe haven assets against the Indonesian stock market during COVID- 19. Daily closing prices of JKSE, Bitcoin, Ethereum, Litecoin, and Ripple were used, then the GARCH model was implemented in the forecasting. DCC-GARCH model, followed by dummy variable regression, will be applied to the return data to evaluate the safe haven property. The prediction projected Bitcoin as the most profitable asset andRipple as the riskiest. The analysis and robustness test suggested that none of these cryptocurrencies were safe haven assets during the whole observation. This indicates that investors who intend to seek safe haven investments were advised against investing in these cryptocurrencies.
Next to artificial intelligence and big data, blockchains have emerged as one of the most oft-cited technologies associated with the digital economy. Leading technology companies have recently contributed to making the technology used more widely by developing integrated blockchain offerings. The emergence of such services yet strikingly clashes with the original stated goal of the technology to remove any form of central political authority, such as the one companies behind these new services can represent. How should we then understand the embrace of blockchains by companies that this technology was notably supposed to displace? Using the concept of infrastructure from Science and Technology Studies, we argue that these companies are not merely adopting the technology but actively promoting a new assemblage of socio-technical devices to reassert their authority over how information is exchanged online. Based on a comparative analysis of the technical documentation of Ethereum and Amazon Web Services (AWS) blockchain services, we highlight how actors contributing to building digital infrastructures regulate their users' behavior by affording them different capacities and constraints. We moreover show how by pursuing its commercial interest, AWS supported a corporate form of governance historically promoted by the United States to oversee the digital economy.
The existing agriculture system is having several components such as supply chain management, crop insurance, the shipment of goods, and it involves numerous untrusted stakeholders such as users (farmers, retailers, customers, wholesalers, etc.), agencies (bank, insurance company) and regulators (assessor, surveyors). Due to the active engrossment of the middle man (mostly human beings or agencies operated by human beings) some key issues are raised such as transparency, timeliness, traceability, security, and immutability resulting in financial loss, crop contamination, and spoilage. Secure distributed public ledger technology and decentralized computing paradigm make Blockchain an appropriate alternative to resolve these issues and to achieve profitability & trust for all its stakeholders. In this research, we intend to propose a Blockchain-based mechanism viz. AgriOnBlock which would address the issues mentioned in the agriculture sector by connecting various stakeholders through the usage of IoT devices and smart contracts in Ethereum. We further discuss implications, constraints (methodological, awareness related, regulatory, etc.), and potential for actual adoption of AgriOnBlock.
Purpose After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a misunderstanding on the cryptocurrency market response. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the Islamic and conventional cryptocurrency dynamics during the COVID-19 pandemic. We, specifically, examine the associate bubbles and feedbacks effects. Design/methodology/approach This paper developed a novel methodology that detects market bubbles using the statistical indicators defined by Psychological (PSY) tests. It also investigated the effect of the Federal Open Market Committee (FOMC) announcements on conventional and Islamic cryptocurrencies compatible with Islamic laws “Shari’ah” by using the event-driven regression. Findings The empirical results show that the FOMC announcements have a positive significant effect after one day of the event and a negative effect before two days of the announcement on the conventional cryptocurrency markets. However, the reaction of Islamic cryptocurrencies to these events is not significant except for Hello Gold after one day of the announcement. Besides, the Hello Gold and X8X cryptocurrencies present no bubbles during this period. However, Bitcoin and Ethereum markets have short-lived bubbles. Research limitations/implications The main contribution of this study is the investigation of the response and vulnerability to pandemic shocks of a new category of cryptocurrencies backed by tangible assets. This work has practical implications as it provides new insights into trading opportunities and market reactions. Originality/value To our knowledge, this work is the first study that compares the response of Islamic and conventional cryptocurrency markets to FOMC announcements during the COVID-19 pandemic and examines the presence of bubbles in these markets. Besides, the originality of this work is derived from the novelty of the data employed and the method used (PSY tests) in this study.
The rise of Ethereum and other blockchains that support smart contracts has led to the creation of decentralized exchanges (DEXs), such as Uniswap, Balancer, Curve, mStable, and SushiSwap, which enable agents to trade cryptocurrencies without trusting a centralized authority. While traditional exchanges use order books to match and execute trades, DEXs are typically organized as constant function market makers (CFMMs). CFMMs accept and reject proposed trades based on the evaluation of a function that depends on the proposed trade and the current reserves of the DEX. For trades that involve only two assets, CFMMs are easy to understand, via two functions that give the quantity of one asset that must be tendered to receive a given quantity of the other, and vice versa. When more than two assets are being exchanged, it is harder to understand the landscape of possible trades. We observe that various problems of choosing a multi-asset trade can be formulated as convex optimization problems, and can therefore be reliably and efficiently solved.
The rise of Ethereum and other blockchains that support smart contracts has\nled to the creation of decentralized exchanges (DEXs), such as Uniswap,\nBalancer, Curve, mStable, and SushiSwap, which enable agents to trade\ncryptocurrencies without trusting a centralized authority. While traditional\nexchanges use order books to match and execute trades, DEXs are typically\norganized as constant function market makers (CFMMs). CFMMs accept and reject\nproposed trades based on the evaluation of a function that depends on the\nproposed trade and the current reserves of the DEX. For trades that involve\nonly two assets, CFMMs are easy to understand, via two functions that give the\nquantity of one asset that must be tendered to receive a given quantity of the\nother, and vice versa. When more than two assets are being exchanged, it is\nharder to understand the landscape of possible trades. We observe that various\nproblems of choosing a multi-asset trade can be formulated as convex\noptimization problems, and can therefore be reliably and efficiently solved.\n
The study presents a blockchain-based incentive mechanism intended to encourage those in underserved communities to engage with healthcare services. The smart healthcare system, which is the result of the amalgamation of advanced technologies, has emerged recently and is increasingly seen as essential to meet the needs of modern society. An important part of the healthcare system is the prescription management system, but studies show that prescription affordability and accessibility play a part in creating unequal access for underserved communities. This is a form of unequal access that results in those living in underserved communities to become disengaged from accessing healthcare services. In New Zealand, the prescription management system plays a crucial role and this study seeks to address the issue by presenting the BlockPres framework, which uses a novel incentive mechanism to encourage patients to participate and engage with services in order to be rewarded. The blockchain attribute of immutability in BlockPres enhances equality and participation by providing sophisticated authorisation and authentication capabilities for healthcare providers and patients. BlockPres empowers the patient by assigning ownership or control of some patient information to the patient. A simulation is carried out using the Ethereum blockchain and the evaluation of successful transaction completion and superficial performance assessment demonstrates that the blockchain would be sufficient to cope with the needs of a prescription management system. Furthermore, for the simulation, a BlockPres Smart Contract is developed using solidity and implemented in Remix. The Ropsten network is used as the simulation environment and the initial results show that the proposed incentive mechanism mitigates unequal access.
Abstract Existing models for non-interactive MPC cannot provide full privacy for inputs, because they inherently leak the residual function (i.e., the output of the function on the honest parties’ input together with all possible values of the adversarial inputs). For example, in any non-interactive sealed-bid auction, the last bidder can figure out what was the highest previous bid. We present a new MPC model which avoids this privacy leak. To achieve this, we utilize a blockchain in a novel way, incorporating smart contracts and arbitrary parties that can be incentivized to perform computation (“bounty hunters,” akin to miners). Security is maintained under a monetary assumption about the parties: an honest party can temporarily supply a recoverable collateral of value higher than the computational cost an adversary can expend. We thus construct non-interactive MPC protocols with strong security guarantees (full security, no residual leakage) in the short term. Over time, as the adversary can invest more and more computational resources, the security guarantee decays. Thus, our model, which we call Gage MPC, is suitable for secure computation with limited-time secrecy, such as auctions. A key ingredient in our protocols is a primitive we call “Gage Time Capsules” (GaTC): a time capsule that allows a party to commit to a value that others are able to reveal but only at a designated computational cost. A GaTC allows a party to commit to a value together with a monetary collateral. If the original party properly opens the GaTC, it can recover the collateral. Otherwise, the collateral is used to incentivize bounty hunters to open the GaTC. This primitive is used to ensure completion of Gage MPC protocols on the desired inputs. As a requisite tool (of independent interest), we present a generalization of garbled circuit that are more robust: they can tolerate exposure of extra input labels. This is in contrast to Yao’s garbled circuits, whose secrecy breaks down if even a single extra label is exposed. Finally, we present a proof-of-concept implementation of a special case of our construction, yielding an auction functionality over an Ethereum-like blockchain.
Nuke Puji Lestari, Yusuf Durachman, Srie Watini, Shofiyul Millah
Banyak pengguna menggunakan internet sebagai alat untuk layanan informasi yang lebih baik di lembaga pendidikan. Jaringan ini tidak memiliki penyedia layanan yang bertindak sebagai otoritas pusat dan pengguna memiliki kontrol lebih besar atas informasi mereka sehingga tidak ada pihak ketiga. Sehingga diusulkan sebagai solusi alternatif untuk sistem pembelajaran jaringan terpusat saat ini menggunakan Decentralized Online Educations (DOE). Banyak DOE telah diusulkan, namun keberadaan layanan Decentralized Online Educations (DOE) membutuhkan solusi terdistribusi yang efisien untuk melindungi privasi pengguna. Dalam beberapa tahun terakhir, banyak teknologi blockchain telah diimplementasikan ke dalam sistem pembelajaran sehingga sangat cocok untuk institusi pendidikan yang digunakan untuk menyelesaikan masalah privasi dalam sistem desentralisasi. Pada platform ini, menggunakan teknologi blockchain sebagai sistem penyimpanan, dan materi pembelajaran yang bersifat publik. Dalam studi ini, buat kerangka kerja kontrol akses yang dapat dikelola dan diaudit untuk Decentralized Online Educations (DOE) menggunakan teknologi blockchain untuk membahas definisi kebijakan privasi. Kunci publik yang digunakan oleh pemilik sumber daya menggunakan dari subjek untuk menentukan kebijakan akses dapat diaudit menggunakan Access Control List (ACL), sedangkan untuk mendekripsi data pribadi setelah izin akses divalidasi di blockchain menggunakan kunci pribadi yang terkait dengan akun Ethereum subjek. Untuk memberikan evaluasi dari pendekatan ini, gunakan testnet Rinkeby Ethereum untuk mengimplementasikan Kontrak Cerdas. Dan hasil dari percobaan ini dapat menunjukkan bahwa Access Control List (ACL) yang diusulkan menggunakan Attribute-Based Access Control (ABAC) dalam sistem pembelajarannya. Untuk mewujudkannya, diperlukan Access Control List (ACL).
Blockchain is a method of storing data that makes it extremely difficult, if not impossible, to edit, hack, or update the system. As time passes, blockchain technology becomes more popular, and blockchain-based applications, also known as DApps, which will be used in this article, are becoming more widely recognised. We will construct a chat application based on a decentralised network in this article to eliminate its absolute reliance on centralised players. On a peer-to-peer network like Ethereum, the actual message and data will be kept. To offer decentralised storage and efficient lookup, we will employ a blockchain and distributed hash table (DHT). which will describe what we will do, which is a trendy issue among academics and trades. Except for the fact that DApps are important, we currently have a limited grasp of DApps and nature. To close the data gap, this paper presents a file for the most comprehensive blockchain-based DApps analysis to date, which includes 995 Ethereum DApps data and 29,846,075 dealings logs above them. We usually do a descriptive investigation of Dapp preferences, characterise patterns of how Dapps use good contracts to gain access to fundamental blockchain, and evaluate the results issues with the post and misuse of DApps In support of the findings, we propose a large number of Results for DApp users to choose the best DApps. Dapp developers must work harder in order to create more efficient DApps, and vendors must likewise support them.
Abstract The General Data Protection Regulation highlights the principle of data minimization, which means that only data required to successfully accomplish a given task should be processed. In this paper, we propose a Blockchain-based scheme that allows users to have control over the personal data revealed when accessing a service. The proposed solution does not rely on sophisticated cryptographic primitives, provides mechanisms for revoking the authorization to access a service and for guessing the identity of a user only in cases of need, and is compliant with the recent eIDAS Regulation. We prove that the proposed scheme is secure and reaches the expected goal, and we present an Ethereum-based implementation to show the effectiveness of the proposed solution.
Lasse Berntzen, Qian Meng, Boban Vesin, Marius Rohde Johannessen · 6 authors
This paper shows how the Ethereum blockchain can register settlements between an aggregator and prosumers in a smart grid. By providing flexible use of electricity to the aggregator, customers get rewarded. The flexibility is valuable for the aggregator since the power infrastructure may be used more efficiently. Blockchain is an exciting technology for handling settlements which, however, also has some clear limitations. For example, the cost per transaction on the public Ethereum blockchain is too high compared to the value of the actual transactions. A private blockchain is an alternative but removes some of the original benefits of using the public blockchain. The paper concludes that blockchain is a promising technology, and a private blockchain is more suitable for transactions containing minimal amounts.
The development of information technology has penetrated various areas. This is driven by improved service, rapid increase in information needs and decision making. General elections that are held every time always leave problems about securities and speed of recapitulation. This is because the process is done in the traditional way. This research tries to apply blockchain technology to the e-Voting system security engineering process so that it creates a votes recapitulation process that is fast, accurate and accompanied by transparency values to maintain the reliability of the existing vote and maintain the confidentiality of the vote data being transacted. Transparency and confidentiality of voter data is a fundamental value in general elections or voting that must exist. Seeing this, blockchain technology deserves to be applied because the principles that needed can be met by applying this technology to the e-Voting system.
This letter revisits the time-series relation between cryptocurrency prices and forward inflation expectations. Using wavelet time-scale techniques, a positive link between cryptocurrencies and forward inflation rates is identified, focused on a brief period surrounding the onset of the COVID-19 pandemic. This coincides with a rapid and synchronized decrease in cryptocurrency prices and forward inflation expectations, followed by a swift recovery to pre-crisis levels. Outside of the crisis period, we find no clear evidence of any inflation hedging capacity of Bitcoin or Ethereum during times of increasing forward inflation expectations.
Asif Bhat, Rizal Mohd Nor, Md Amiruzzaman, Md. Rajibul Islam
Blokchain is used in a variety of applications where trustworthy computing is\nre-quired. Trade finance is one of these areas that would benefit immensely\nfrom a decentralized way of doing transactions. This paper presents the\npreliminary as-sessment of Accepire-BT, a software platform developed for the\npractice of col-laborative Trade Finance. The proposed solution is enforced by\nsmart contracts using Solidity, the underlying programming language for the\nEthereum block-chain. We evaluated the performance in the Rinkeby test network\nby using Remix and MetaMask. The results of the preliminary trial show that\nsmart contracts take less than one minute per cycle. Also, we present a\ndiscussion about costs for us-ing the public Ethereum Rinkeby network.\n
Blockchain is currently one of the fastest-growing technologies in the field of Computer Science. It has found a prevalent use in financial applications like cryptocurrency, for example, Bitcoin and Ethereum. They have been able to bring an unforeseen disruption in the field of finance. However, permissionless Blockchains like these have some downsides, namely the computation cost of the Proof of Work algorithm, maximum allowed size for a block, decrease in intelligibility with the increase of the number of blocks in the chain, domination of nodes with higher computing power as miners and validators. These factors have restricted the adoption of permissionless blockchain technology outside the field of finance, such as in medical or legal fields. This paper proposes a solution to these problems using a permissioned blockchain. It does not require a computationally expensive consensus mechanism as permissioned chains call for trust between participating organizations which is achieved via exclusive invitations. We have utilized a third-party orderer to maintain the trust between organizations.
Abstract Internet of Things (IoT) has revolutionized the digital world by connecting billions of electronic devices over the internet. IoT devices play an essential role in the modern era when conventional devices become more autonomous and smart. On the one hand, high‐speed data transfer is a major issue where the 5G‐enabled environment plays an important role. On the other hand, these IoT devices transfer the data by using protocols based on centralized architecture and may cause several security issues for the data. Merging artificial intelligence to 5G wireless systems solves several issues such as autonomous robots, self‐driving vehicles, virtual reality, and engender security problems. Building trust among the network users without trusting third party authorities is the system's primary concern. Blockchain emerged as a key technology based on a distributed ledger to maintain the network's event logs. Blockchain provides a secure, decentralized, and trustless environment for IoT devices. However, integrating IoT and blockchain also has several challenges; for example, major challenge is low throughput. Currently, the ethereum blockchain network can process approximately 12 to 15 transactions per second, while IoT devices require relatively higher throughput. Therefore, blockchains are incapable of providing functionality for a 5G‐enabled IoT based network. The limiting factor of throughput in the blockchain is their network. The slow propagation of transactions and blocks in the P2P network does not allow miners and verifiers to fastly mine and verify new blocks, respectively. Therefore, network scalability is the major issue of IoT based blockchains. In this work, we solved the network scalability issue using blockchain distributed network while to increase the throughput of blockchain, this article uses the Raft consensus algorithm. Another most important issue with IoT networks is privacy. Unfortunately, the blockchain distributed ledgers are public and sensitive information is available on the network for everyone are private, but in such cases, third party editing is not possible without revealing the original contents. To solve privacy issues, we used zkLedger as a solution that is based on zero knowledge‐based cryptography.
Zaghum Umar, Francisco Jareño, María de la O González
This research explores the impact of COVID-19-related media coverage on the dynamic return and volatility connectedness of the three dominant cryptocurrencies (Bitcoin (BTC), Ethereum (ETH) and Ripple (XRP)) and the fiat currencies of the euro, GBP and Chinese yuan. The sample period covers the first and second devasting waves of the COVID-19 pandemic crisis and ranges from January 1, 2020, to December 31, 2020. The dynamic return and volatility connectedness measures are estimated using the time varying parameter-VAR approach. Our return connectedness analysis shows that the media coverage index (only before the first wave) and the cryptocurrencies are the net transmitters of shocks while the fiat currencies are the net receivers of shocks. Similar results are obtained in terms of volatility, except for the euro, which shows a clear net receiver profile in January and February. This fiat currency (the euro) became a net transmitter in March and during the first wave of the COVID-19 crisis, which possibly shows the virulence of the pandemic on the European continent. Moreover, the most relevant differences between the net dynamic (return and volatility) connectedness of these two groups of currencies are focused on the beginning of the sample period, just before the first wave of the SARS-CoV-2 pandemic crisis, although some differences are observed during the first and second waves of the coronavirus outbreak.
Anti-piracy is fundamentally a procedure that relies on collecting data from the open anonymous population, so how to incentivize credible reporting is a question at the center of the problem. Industrial alliances and companies are running anti-piracy incentive campaigns, but their effectiveness is publicly questioned due to the lack of transparency. We believe that full transparency of a campaign is necessary to truly incentivize people. It means that every role, e.g., content owner, licensee of the content, or every person in the open population, can understand the mechanism and be assured about its execution without trusting any single role. We see this as a distributed system problem. In this paper, we present Argus, a fully transparent incentive system for anti-piracy campaigns. The groundwork of Argus is to formulate the objectives for fully transparent incentive mechanisms, which securely and comprehensively consolidate the different interests of all roles. These objectives form the core of the Argus design, highlighted by our innovations about a Sybil-proof incentive function, a commit-and-reveal scheme, and an oblivious transfer scheme. In the implementation, we overcome a set of unavoidable obstacles to ensure security despite full transparency. Moreover, we effectively optimize several cryptographic operations so that the cost for a piracy reporting is reduced to an equivalent cost of sending about 14 ETH-transfer transactions to run on the public Ethereum network, which would otherwise correspond to thousands of transactions. With the security and practicality of Argus, we hope real-world anti-piracy campaigns will be truly effective by shifting to a fully transparent incentive mechanism.
Open access
2 source records
cs.CR
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques