Classified protection is one of primary security policies of information system in many countries. With the increasing popularity of blockchain in various fields of applications, it is extremely necessary to promote classified protection for blockchain's risk assessment in order to push forward the sustainable development of blockchain. Taking the Level 3 in Chinese classified protection 2.0 as an example, this paper proposes the common evaluation rules on blockchain to ensure that blockchain can meet the needs of countries to build it as critical infrastructure. Both assessment requirements and enforcement proposals are presented and analyzed from the standpoint of blockchain's core technologies, e.g., peer-to-peer network, distributed ledger, contract's scripting system, and consensus mechanism. Moreover, the assessment results on three main platforms, Bitcoin, Ethereum, and Hyperledger, are summarized and analyzed in compliance with the control points specified in the level 3. Our investigation indicates that the current blockchain is able to satisfy the requirements of evaluation items in many aspects, such as software fault tolerance, resource control, backup and recovery, but further improvements are still needed for some aspects, including security audit, access control, identification and authentication, data integrity, etc., in order to satisfy the requirements of important fields on national security, economic development and human life.
Cryptocurrencies (e.g., Bitcoin and Ethereum), which promise to become the future of money transactions, are mainly implemented with blockchain technology. However, blockchain suffers from scalability issues. Sharding is the leading solution for blockchain scalability. Sharding splits the blockchain network into sub-chains called shards/committees. Each shard processes a sub-set of transactions, rather than the entire network processing all transactions. This raises security issues for sharding-based blockchain protocols. In this paper, we propose a novel methodology to analyze the security of these protocols (e.g., OmniLedger and RapidChain). In particular, this methodology estimates the failure probability of one sharding round taking into consideration the failure probabilities of all shards. To illustrate the effectiveness of the estimated failure probability, we conduct a numerical analysis of our methodology based on a huge number of trials. Finally, we compute confidence intervals to accurately estimate the failure probability and compare our methodology with existing approaches.
Since it was invented by Satoshi Nakamoto in 2008, Bitcoin has drawn considerable attention both from the financial industry and government supervisory departments, and there is no unanimity on Bitcoin’s nature in the academic field. Some people may think Bitcoin is more like an asset than a currency. And investors’ motivations for incorporating Bitcoin into their portfolios may vary. Might there be a better way to deal with the risk-detection issue associated with such a unique and ambiguous object? The copula-GARCH method has been proven in much of the literature to be a better way than the traditional ways to estimate the value at risk (VaR) of portfolios. When it comes to a portfolio containing Bitcoin, can it still maintain its superiority? In this study, gold and Ethereum were each used to construct a portfolio with Bitcoin. We collected a total of 2,246 daily adjusted closing prices from July 23, 2010, to March 12, 2019. As for the copula-GARCH model, we selected four constant and two time-varying copula models combined with GARCH Student-t residuals to fit the joint distribution of the two assets in the portfolios. The traditional methods refer to the historical simulation, the variance-covariance method, the EWMA method, and the univariate GARCH VaR method. We adopted each method to compute corresponding one-day VaRs. Our results indicated that for the portfolios containing Bitcoin and Ethereum, the copula-GARCH method performed better than traditional methods, while for the portfolio consisting of Bitcoin and gold, traditional methods performed better. Our results may suggest that the copula-GARCH method may not be suitable in the extremely low correlation case.
Machine learning has recently enabled large advances in artificial intelligence, but these results can be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and maintain them. Published proposals to provide models and data for free for certain tasks include Microsoft Research's Decentralized and Collaborative AI on Blockchain. The framework allows participants to collaboratively build a dataset and use smart contracts to share a continuously updated model on a public blockchain. The initial proposal gave an overview of the framework omitting many details of the models used and the incentive mechanisms in real world scenarios. In this work, we evaluate the use of several models and configurations in order to propose best practices when using the Self-Assessment incentive mechanism so that models can remain accurate and well-intended participants that submit correct data have the chance to profit. We have analyzed simulations for each of three models: Perceptron, Naïve Bayes, and a Nearest Centroid Classifier, with three different datasets: predicting a sport with user activity from Endomondo, sentiment analysis on movie reviews from IMDB, and determining if a news article is fake. We compare several factors for each dataset when models are hosted in smart contracts on a public blockchain: their accuracy over time, balances of a good and bad user, and transaction costs (or gas) for deploying, updating, collecting refunds, and collecting rewards. A free and open source implementation for the Ethereum blockchain and simulations written in Python is provided at https://github.com/microsoft/0xDeCA10B. This version has updated gas costs using newer optimizations written after the original publication.
Crowdsourcing is a process wherein an individual or an organisation utilizes the talent pool present over the Internet to accomplish their task. The existing crowdsourcing platforms and their reputation computation are centralised and hence prone to various attacks or malicious manipulation of the data by the central entity. A few distributed crowdsourcing platforms have been proposed but they lack a robust reputation mechanism. So we propose a decentralised crowdsourcing platform having an immutable reputation mechanism to tackle these problems. It is built on top of Ethereum network and does not require the user to trust a third party for a non malicious experience. It also utilizes IOTAs consensus mechanism which reduces the cost for task evaluation significantly.
Abstract Solidity is the dominant programming language for Ethereum smart contracts. This paper presents a high-level formalization of the Solidity language with a focus on the memory model. The presented formalization covers all features of the language related to managing state and memory. In addition, the formalization we provide is effective: all but few features can be encoded in the quantifier-free fragment of standard SMT theories. This enables precise and efficient reasoning about the state of smart contracts written in Solidity. The formalization is implemented in the SOLC-VERIFY verifier and we provide an extensive set of tests that covers the breadth of the required semantics. We also provide an evaluation on the test set that validates the semantics and shows the novelty of the approach compared to other Solidity-level contract analysis tools.
Utz Nisslmueller, Klaus-Tycho Foerster, Stefan Schmid, Christian Decker
Cryptocurrency off-chain networks such as Lightning (e.g., Bitcoin) or Raiden (e.g., Ethereum) aim to increase the scalability of traditional on-chain transactions. To support nodes in learning about possible paths to route their transactions, these networks need to provide gossip and probing mechanisms. This paper explores whether these mechanisms may be exploited to infer sensitive information about the flow of transactions, and eventually harm privacy. In particular, we identify two threats, related to an active and a passive adversary. The first is a probing attack: here the adversary aims to detect the maximum amount which is transferable in a given direction over a target channel by actively probing it and differentiating the response messages it receives. The second is a timing attack: the adversary discovers how close the destination of a routed payment actually is, by acting as a passive man-in-the middle and analyzing the time deltas between sent messages and their corresponding responses. We then analyze the limitations of these attacks and propose remediations for scenarios in which they are able to produce accurate results.
Smart contracts are computer programs that are deployed on the blockchain and can then be executed. Fees in form of gas have to be paid for deploying a smart contract on the blockchain, depending on the size of the byte code. Additional fees have to be paid, whenever a function of a smart contract is executed, depending on the needed computational steps and required storage space. On the Ethereum blockchain, millions of USD are paid in form of gas fees every single day. Since gas cost can increase if a contract is not well-implemented, there is a lot of incentive to reduce these gas cost in order to save money. We identified 19 optimization strategies from the field of software engineering, which can be applied to Solidity smart contracts in order to reduce the required gas cost. To show how these rules can be used to optimize smart contracts, we developed a prototype. The prototype detects rule violations from 9 of these rules and in addition automatically optimizes 6 of them. The prototype analyzed 3,018 verified open source smart contracts from etherscan.io. We found 471 rule violations in our test data set spread across 204 different contract files. That means, roundabout 6.8% of the data set violated at least one of the rules. We deployed the automatically optimized contracts in a test environment before and after the optimization, to compare the gas usage. We were on average able to save 1,213 gas for deploying an optimized contract version compared to the initial one. For calling an optimized function once, we were able to save on average 123 gas, compared to the initial function call.
Subscriber authentication is a primitive operation in mobile networks required by each operator prior to offering any service to end users. In this paper, we propose a novel blockchain-based Authentication and Key Agreement (AKA) protocol for roaming services in 5G networks. Each Home Network (HN) creates its own smart contract and publishes its address to inform other operators who want to offer roaming services to HN subscribers. All subsequent communication between the HN and Serving Network (SN) is done by calling the function of this smart contract. The proposed protocol eliminates the need for a secure channel between the HN and SN, which is a primary requirement of current 5G AKA protocols. In practice, a secure channel requires the HN and SN to establish a secure session before running the AKA protocol. Further, the proposed protocol leverages the benefits of blockchain, such as auditable log, decentralized architecture, and the prevention of Denial of Service (DoS) attacks. Furthermore, we provide a security proof of the protocol through formal verification using ProVerif. The results show that our scheme tends to preserve user privacy and at the same time provides mutual authentication of the participants. Finally, our evaluation of the Ethereum blockchain shows that the protocol is efficient in terms of both transaction and execution costs.
The global implementation architecture of the traditional stock market distributes responsibilities and data across different intermediaries, including financial and governmental organizations. Each organization manages its system and collaborates with the others to facilitate trading on the stock exchange platform, and typically buy-sell orders go through different parties before settlement. This design architecture that involves a complex chain of intermediaries has several limitations and shortcomings, such as a single point of failure, a longer time for financial settlements, and weak transparency. Blockchain technology consists of a network of computer nodes that securely share a common ledger without the need of having any kind of intermediaries. In this paper, we present a novel blockchain-based architecture for a fully decentralized stock market. Our architecture is based on a private Ethereum blockchain to create a consortium network leveraging organizations that are already involved in the traditional stock exchange to act as validating nodes. In our architecture, the stock exchange trading logic is completely implemented on a smart contract, while considering the existing governmental market regulations. Since the new platform does not introduce significant changes to the stock exchange trading logic and does not eliminate any of the traditional parties from the system, our proposal promotes efficient adoption and deployment of decentralized stock exchange platforms. In addition, we present a proof of concept implementation of the new architecture, including the smart contract for trade exchange, as well as a virtualization-based test network to assess the platform performance. The test network consists of virtual nodes that run the developed stock exchange smart contract where we measure the buy-sell orders throughput and latency under different network sizes and trading workload scenarios. The obtained results have shown that the proposed trading platform can reach a throughput of 311.8 tx/sec, which is equivalent to 89% of the optimal throughput when the sending rate is 350 tx/sec. This throughput is largely sufficient to meet the requirement of major stock exchanges, such as Singapore stock market.
Die Blockchain Technologie hat das Potential die Wirtschaft im Zeitalter der Digitalisierung zu revolutionieren. In zentralisierten Organisationen werden die Entscheidungen von einem Verantwortlichen oder einer Gruppe getroffen. In der Blockchain gibt es keinen bestimmten Entscheidungsträger. Um eine Entscheidung zu treffen, muss ein Konsens erreicht werden. Um diesen Konsens zu erreichen, wird von jeder Blockchain Plattform ein so genannter Konsens-Mechanismus eingesetzt. Damit Blockchains ihr volles ökonomisches Potential ausschöpfen können, muss eine gute Skalierbarkeit gegeben sein. Doch dazu müssen Kompromisse in anderen Bereichen eingegangen werden. Das Blockchain-Trilemma besagt, dass man die drei Haupteigenschaften Skalierbarkeit, Sicherheit und Dezentralität immer zulasten der anderen erreicht, bzw. dass alle drei Eigenschaften nicht gleichzeitig maximiert werden können. Die implementierten Konsens-Mechanismen versuchen dieses Dilemma mit unterschiedlichen Ansätzen zu lösen. Daher sind sie einer der wichtigsten Aspekte sowie Unterscheidungsmerkmale der Blockchain Plattformen. Diese Arbeit bietet einen Überblick sowie eine technische Analyse über die zur Zeit existierenden Konsens-Mechanismen. Darüber hinaus werden Smart Contract Plattformen analysiert und die dort eingesetzten Konsens-Mechanismen detailliert beleuchtet. Außerdem wird die Umstellung des Konsens-Mechanismus von Proof of Work zu Proof of Stake in der Ethereum-Plattform anhand Ihres Einflusses auf zukünftige Smart Contracts analysiert. Die Analyse liefert einen Überblick über 62 Konsens-Mechanismen und 21 Smart Contract-Plattformen die im Moment eingesetzt werden. Weiter werden Kriterienkataloge vorgestellt, welche für den Vergleich von Smart Contract-Plattformen sowie deren Konsens-Mechanismen eingesetzt werden können.
Developing compiler optimizations, especially for new, rapidly evolving smart contract languages, can be onerous and error-prone, but is especially important for smart contracts, where deployment and execution directly translate to monetary cost and which cannot change once deployed. One common optimization technique is the use of peephole optimizations, replacement rules that are applied using pattern-matching. These rules are normally constructed using human expertise, which is both time-consuming and far from systematic in exploring opportunities for optimization. In this work we propose a pipeline to automatically populate the peephole optimizer of a smart contract compiler. We apply superoptimization to an existing code base to obtain sequences of instructions, which can be replaced by cheaper, observationally equivalent instructions. We then generate peephole optimization rules by extracting the underlying patterns of these optimizations. We provide a case study of our approach and a prototype implementation for bytecode of the Ethereum Virtual Machine, the tool ppltr, which combines the superoptimizer ebso and the rule generator sorg. Then we evaluate our approach by generating and applying nearly 1k peephole optimization rules extracted from 2k optimizations obtained from deployed bytecode.
H. M. N. Dilum Bandara, Shiping Chen, Mark Staples, Xiwei Xu · 10 authors
Data from our modified Geth client used with http://ethviewer.live. Contains block, uncles, transactions (1st arrival to transaction pool and in blocks), addresses, and smart contracts data from public Ethereum network. Data between blocks 4,728,040 (2017-12-13) to 10,859,203 (2020-09-14). There are periods of missing data due to node failures and Geth client updates.
With smart contracts, a wide range of applications can be implemented on blockchains. Ethereum stores smart contract byte code with the smart contract ad-dress so, the Ethereum Virtual Machine (EVM) can read and execute transactions correctly. All executed transactions (both successful and failed transactions) are stored on the platform permanently. Failed transactions are thrown by the EVM due to runtime errors and result in monetary waste. The waste from these transactions add up to around 2 million Ethers or $634.2 million. In this thesis, we propose Evitar, a warning algorithm for reducing Ethereum smart contract runtime errors, which has two mechanisms. First, Evitar proposes that users send transactions with the maximum gas allowed to avoid Out of Gas errors. However, this results in an extremely high transaction fee when transactions fail. Second, Evitar analyzes transactions called to each method in smart contracts and marks a method as a method with a high failure rate if the number of failed transactions reaches Evitar’s threshold. This mechanism prevents users from sending and paying for transactions that are likely to fail. We run experiments to evaluate the performance of Evitar by replaying transactions in a private network. The results show that Evitar can reduce failed transactions up to 99.52% compared to sending under default behaviour in exchange for a reduction in successful transactions by 1.78%. The amount of gas used by Evitar is only one-tenth compared to sending under default behaviour. Sending transactions with the maximum gas in Evitar reduces Out of Gas errors by 99.25%. In addition, Evitar can save up to 15.04 GB (82.32%) of storage in the Geth default node and 50.09 GB (50.09%) in the Parity full archive node.
The objective of the study is to determine whether the Bitcoin forks have produced significant effects on the cryptocurrency market. The event study methodology is used in this paper in order to determine the statistical significance of the abnormal return of leading cryptocurrencies after three Bitcoin forks. The forks were viewed as three isolated events, with the estimations windows and the event windows constructed separately for each of them. There were statistically significant negative effects related to the creation of Bitcoin Gold and Bitcoin SV. Contrary to expectations, there was no statistically important effect throught out the most famous Bitcoin forking and emergence of Bitcoin Cash. Although cryptocurrencies are a current topic, the literature lacks quantitative research dealing with price changes. Without quantitative analysis, it is difficult to conclude whether the return change is a consequence of a statistically significant event The analysis would therefore provide the tool to determine the statistical significance of their impact on the market. A small number of observed cryptocurrencies is the main limitation of this research. Future researches could cover a wider scope of the market and include other famous cases of forking, for example, the Ethereum forks.
Guglielmo Maria Caporale, Woo-Young Kang, Fabio Spagnolo, Nicola Spagnolo
This paper provides some comprehensive evidence on the effects of cyber-attacks on the returns, realized volatility and trading volume of five of the main cryptocurrencies (Bitcoin, Ethereum, Litecoin, XRP and Stellar) in 99 developed and developing countries. More specifically, it investigates the effects of four different types of cyber-attacks (cyber-crime, cyber-espionage, hacktivism and cyber-warfare) on four target sectors (government, industry, finance and cryptocurrency exchange). We find that in the US cyber security firms tend to overreact to cyberattacks affecting cryptocurrencies and more wealth is spent on cyber security compared to other countries. Both hacktivism and cyber-warfare have a significant impact on cryptocurrencies. Cryptocurrency exchanges are more vulnerable to cyber-attacks in non-US countries and in the presence of high economic uncertainty and less so if the industry sector is already being targeted. Finally, cryptocurrency investors exhibit risk-loving behaviour when the hash rate and cryptocurrency returns increase and risk-averse one when cyber-attacks target the financial and industry sectors and economic uncertainty is high.
Muhammad Abubakr Naeem, Kashif Saleem, Sheraz Ahmed, Naeem Muhammad · 5 authors
We explore extreme return-volumes dependence among different cryptocurrencies such as Bitcoin, Ethereum, Ripple, and Litecoin by using the Copula approach. We use Student-t, Frank, Clayton, Survival Clayton, Gumbel, and SJC copulas. We filter out margins by using the EGARCH model for return series and GARCH model for volume series. Evidence of significant symmetric dependence between return-volume is not found due to insignificance of student-t and Frank copula parameters. In a return-volume relationship, coefficients of lower tail dependence are significant for Bitcoin, Ripple, and Litecoin which means that low returns are followed by low volumes. Lower tail dependence for the return-volume relationship is stronger than the upper tail dependence for Bitcoin, Ripple, and Litecoin. Moreover, for negative return-volume, left tail dependence coefficients are significant for Ripple and Litecoin, which means that high returns are followed by low volumes for Ripple and Litecoin. Our investigation shows that investors (buyer or seller) are very careful in extreme market conditions for both Ripple and Litecoin. Extreme upper tail and lower tail dependence coefficients are insignificant for Ethereum.
The increasing electric vehicle (EV) penetration in a distribution network triggers the need for EV charging coordination. This paper firstly proposes a hierarchical EV charging coordination model and an algorithm based on Lagrangian relaxation. A barrier to the implementation of the coordination algorithm is that there usually does not exist a reliable coordinator of charging stations. This paper shows that an unreliable coordinator may collude with some charging stations and behave dishonestly by disobeying the coordination algorithm. Thus, the collusion coalition can gain more profits while lowering the profits of others and the total social welfare. To provide reliable coordination of charging stations, a novel blockchain-based coordination platform via Ethereum is established, including a coordination structure and a smart contract. A mathematical analysis is given to show that the proposed platform can mitigate the collusion behaviors in the coordination. Simulation results show the consequence of collusion and how blockchain can prevent the collusion.
The study aims at understanding the current scenario of blockchain education and whether it is meeting the increasing demand of blockchain professionals in the job market. In addition, it also provided a comparison between Ethereum and Hyperledger and analyzed the one best suited for better academic curriculum design. By drawing from various sources of data, including journals, articles, reports, the study provided critical insights into the various aspects of a blockchain education. It assesses the existing curriculum on the blockchain that includes courses and programs from various renowned universities and business schools. The study reveals that although the courses are comprehensive in developing theoretical knowledge of the learner, it does not provide the scope for practical skill development. This gap reflects the skill-shortage of blockchain professionals in the job market. To address this, the research also provides some guidelines for developing a comprehensive pedagogical structure using Hyperledger technology. The discussion also highlights the benefits associated with Hyperledger and the way it can foster active learning among the learners. Finally, the researcher also provided the practical and theoretical implications of the study and assessed its limitations directing on the future course of research.
Mazin Debe, Khaled Salah, Muhammad Habib ur Rehman, Davor Svetinović
Fog computing systems are designed to provide localized computation, storage, and communication services in close proximity to the endpoint mobile and IoT devices. Fog service providers typically monetize their service usage via centralized payment mechanisms in unverifiable and non-transparent manner. Therefore, there exists a need for a trust-enabling payment mechanism whereby fog service providers should be incentivized or penalized based upon the continuous feedback from endpoint devices. We propose a decentralized reverse-bidding scheme developed using the key features of blockchain and smart contracts. We develop a solution that allows the users or devices to initiate the bidding process by making a request for services to be provided by nearby public fog nodes, and these fog nodes to make bid offers in return. The proposed scheme ensures that all fog nodes on the network can equally and fairly make offers to win the bid. The bidding process incorporates the automated payments at the end of the service. Our solution is implemented using Ethereum smart contracts. It also integrates a reputation system for fog nodes and imposes a penalty for misbehaving nodes. Our solution is fully decentralized and provides a high level of trust, transparency, and security. In the paper, we present the system architecture, implementation details, and show the correct functionality of the overall proposed solution. In addition, we provide performance, cost, and security analyses of the smart contract code to demonstrate its effectiveness and robustness against major security concerns. The results show that the cost of running the smart contract remained less than three cents with the current Ethereum price (i.e., 183.22 USD/Eth). We have also made our smart contract code publicly available on Github.
Multi-party authorization (MPA) typically involves multiple parties to control and grant access to shared data. MPA is used to solve the insider’s attack problem by ensuring that a single authority or party is not acting alone. Currently, almost all existing implementations of MPA are centralized and fall short in providing logs and events related to provenance of granting permissions in a trusted, secure, immutable, auditable, and decentralized manner. Moreover, for sharing data, proxy re-encryption algorithms are often used to give secure access to encrypted shared data. These schemes and algorithms are also centralized and cannot be trusted. In this paper, we propose a fully decentralized blockchain-based solution in which MPA is implemented using Ethereum smart contracts, and proxy re-encryption algorithms (which are computationally expensive) are implemented using multiple oracles to give access to encrypted shared data stored on a public and decentralized storage platform, such as the Interplanetary File Systems (IPFS). The smart contracts help to validate results based on the majority of encrypted results determined by the oracles. For this, we incorporate reputation mechanisms in the proposed smart contracts to rate the oracles based on their malicious and non-malicious behaviors. We present algorithms along with their full implementation, testing, and validation details. We evaluate the proposed system in terms of security, cost, and generalization to show its reliability and practicality. We make the smart contract source code publicly available on Github.