Michela Moschella, Pietro Ferraro, Emanuele Crisostomi, Robert Shorten
In this paper we propose a stochastic decentralized algorithm to recommend\nthe most convenient Charging Station (CS) to Plug-in Electric Vehicles (PEVs)\nthat need charging. In particular, we use different cost functions to describe\nthe possibly different priorities of PEV drivers, such as the preference to\nminimize charging costs, charging times, or the distance between them and the\nCS. For this purpose, we leverage on an IoT architecture based on a\npermissioned Distributed Ledger Technology (DLT) to enforce compliance of\ndrivers and reduces the occurrence of detrimental misbehaviours of drivers.\nExtensive simulations performed with the mobility simulator SUMO in realistic\ncity-wide networks have been provided to illustrate how the proposed PEV\nassignment procedure works in practice, and to validate its performance.\n
Iqbal Thonse Hawaldar, T M Rajesha, Lolita Jane Dsouza
This study examines the weak form of efficiency of the exchange rate of cryptocurrencies against US Dollar. The study is based on the exchange rate of Bitcoin and Litecoin against US Dollar from 2013 to 2017. The data is tested for heteroscedasticity, and the efficiency of these coin market is analysed using unit root and stationary tests such as Augmented Dickey Fuller (ADF) test, Philips Perron (PP) test and Kwiatkowski Phillips Schmidt Shin (KPSS) tests. The results of the study reveal that the Bitcoin and Litecoin exchange rate exhibit a random walk. Speculation helps for the rapid growth of these currency markets. It is advisable for the investors to invest for short term to get higher returns rather than for the long term. Investment in cryptocurrencies involves market shocks due to its unpredictable nature.
To implement a blockchain, the trend is now to integrate a non-trivial Byzantine fault tolerant consensus algorithm instead of the seminal idea of waiting to receive blocks to decide upon the longest branch. After a decade of existence, blockchains trade now large amounts of valuable assets and a simple disagreement could lead to disastrous losses. Unfortunately, Byzantine consensus solutions used in blockchains are at best proved correct "by hand" as we are not aware of any of them having been formally verified. In this paper, we propose two contributions: (i) we illustrate the severity of the problem by listing six vulnerabilities of blockchain consensus including two new counter-examples; (ii) we then formally verify two Byzantine fault tolerant components of Red Belly Blockchain using the ByMC model checker. First, we specify a simple broadcast primitive in 116 lines of code that is verified in 40 seconds on a 2-core Intel machine. Then, we specify a blockchain consensus algorithm in 276 lines of code that is verified in 17 minutes on a 64-core AMD machine using MPI. To conclude, we argue that it has now become both relatively simple and crucial to formally verify the correctness of blockchain consensus protocols.
A key aspect of Federated Learning (FL) is the requirement of a centralized aggregator to maintain and update the global model. However, in many cases orchestrating a centralized aggregator might be infeasible due to numerous operational constraints. In this paper, we introduce BAFFLE, an aggregator free, blockchain driven, FL environment that is inherently decentralized. BAFFLE leverages Smart Contracts (SC) to coordinate the round delineation, model aggregation and update tasks in FL. BAFFLE boosts computational performance by decomposing the global parameter space into distinct chunks followed by a score and bid strategy. In order to characterize the performance of BAFFLE, we conduct experiments on a private Ethereum network and use the centralized and aggregator driven methods as our benchmark. We show that BAFFLE significantly reduces the gas costs for FL on the blockchain as compared to a direct adaptation of the aggregator based method. Our results also show that BAFFLE achieves high scalability and computational efficiency while delivering similar accuracy as the benchmark methods.
Scott Thiebes, Matthias Schlesner, Benedikt Brors, Ali Sunyaev
Modern life sciences with their highly sensitive omics data face several challenges regarding data storage and sharing [ 1 , 2 ]. On the one hand data must be protected to preserve the privacy of those individuals who contributed their data to research. On the other hand, omics data’s true value is only to be realized if shared with as many researchers as possible. In an ideal world, patients can flexibly control access to their personal data on a case-by-case basis [ 3 ]. However, granting and revoking access to data is a slow and tedious process within the current life sciences research paradigm, where most data is either stored on central controlled-access data repositories or kept locally within the respective research groups [ 3 ].
Open access
Innovative Microfluidic and Catalytic Techniques Innovation
Abstract Cryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies. In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.e. addresses do not tend for transact with a particular type of addresses of higher or lower degree, and the degree sequence of their transaction graph follows the power law distribution.
Background: This study attempts to understand the importance of applying E-learning resources through evaluating the importance of said-resources in the differences appearing in the translation quality of texts trained to the students through various educational references. Objectives: To achieve the purpose, the study was conducted at Islamic Azad University-Tehran Science and Research branch during the second semester of academic year 2018 - 19. Methods: The evaluation of translation quality of the students who trained translation via traditional references and E-learning resource tools was conducted at the textual level according to the Sager’s general classification for three levels of gravity of errors considering distortion of sense, omission, and minor errors using one way ANCOVA to determine a statistically significant difference in the learner’s outcome through controlling the potential effect of translation pretest. Results: For both traditional and E-learning references in translation training, the scorings of the two translation raters were consistent since the intraclass correlation (α) was 0.933 (> 0.70). The two groups of the study were significantly different from one another via obtaining the mean of 15.51 in the E-learning resources group of the participants in comparison with the mean obtained in the traditional references group which was 13.75 in the early observation of the descriptive statistics. Besides, the P value of 0.001 (< 0.050) retrieved from the result of One-way ANCOVA, represented the significant effect of training translation via applying E-learning in comparison to the traditional referenced training. The significance value of .001, which was smaller than 0.050, indicated the fact that our groups were significantly different. The proof to the claim was given strength from the results of the post hoc test for the dependent variable of the study (translation posttest), in which the means of 15.547 (for the control group) and 16.073 (for the experimental group) in the multiple measurements of P value (0.001) was calculated based on the 95% of confidence interval and standard error of 0.175. Accordingly, the translation training via E-learning resources made a statistically significant difference in the learning outcome of the students, the quality of students’ translation, while controlling the effect of the pretest. Also, the effect size of 0.244 revealed the strength of independent variable as an appropriate numerical value for indicating the efficacy of the treatment-training translation via applying E-learning resources. Conclusions: The consistency of quality assurance in translation could be achievable via E-learning resources; however it is not possible to consider all the resources as the appropriate material within all educational contexts with various instructional designs. Thus, the use of E-learning resources, as the necessary factor in reconfiguring the universities for the future through updated instructional designs should be preserved by the teachers and students regarding the necessary adaptations required in the local contexts of training translation. The research implications are basically referring the stake holders in developing instructional designs to consider the importance of E-learning resources in the training procedures applied by the instructors to provide various courses including translation. However, it is necessary for the policy makers to pave the grounds to settle the required platforms for the use of such resources within educational contexts concerning their applicability in the local context.
Off-chain transaction networks can mitigate the scalability issues of today's trustless electronic cash systems such as Bitcoin. However, these peer-to-peer networks also introduce a new attack surface which is not well-understood today. This paper identifies and analyzes, a novel Denial-of-Service attack which is based on route hijacking, i.e., which exploits the way transactions are routed and executed along the created channels of the network. This attack is conceptually interesting as even a limited attacker that manipulates the topology through the creation of new channels can navigate tradeoffs related to the way it attacks the network. Furthermore, the attack also highlights a fundamental design tradeoff for the defender (who determines its own routes): to become less predictable and hence secure, a rational node has to pay higher fees to nodes that forward its payments. We find that the three most common implementations for payment channels in Bitcoin (lnd, C-lightning, Eclair) approach routing differently. We begin by surveying the current state of the Lightning network and explore the routes chosen by these implementations. We find that in the current network nearly 60\% of all routes pass through only five nodes, while 80\% go through only 10 nodes. Thus, a relatively small number of colluding nodes can deny service to a large fraction of the network. We then turn to study an external attacker who creates links to the network and draws more routes through its nodes by asking for lower fees. We find that just five new links are enough to draw the majority (65\% - 75\%) of the traffic regardless of the implementation being used. The cost of creating these links is very low. We discuss the differences between implementations and eventually derive our own suggested routing policy, which is based on a novel combination of existing approaches.
Purpose -The increase in the popularity of cryptocurrency market, various literature figure out the macroeconomic factors that effect the price movements of cryptocurrencies. This research aims to identify the interaction between gold, brent oil and bitcoin. Methodology -The database includes the Daily prices of Bitcoin, gold and brent oil prices between the period of 28.04.2013-23.07.2019 which consist of 484 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by the Impulse-Response Function and Variance Decomposition methods. Findings-The series are found out to be stationary at first difference. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 5 days.
In recent years, increasing attention has been devoted to cryptocurrencies, owing to their great development and valorization. In this study, we propose to analyse four of the major cryptocurrencies, based on their market capitalization and data availability: Bitcoin, Ethereum, Ripple, and Litecoin. We apply detrended fluctuation analysis (the regular one and with a sliding windows approach) and detrended cross-correlation analysis and the respective correlation coefficient. We find that Bitcoin and Ripple seem to behave as efficient financial assets, while Ethereum and Litecoin present some evidence of persistence. When correlating Bitcoin with the other cryptocurrencies under analysis, we find that for short time scales, all the cryptocurrencies have statistically significant correlations with Bitcoin, although Ripple has the highest correlations. For higher time scales, Ripple is the only cryptocurrency with significant correlation.
The intelligent vehicle (IV) has become a promising technology that could revolutionize our life in smart cities sooner or later. However, it yet suffers from many security vulnerabilities. Traditional security methods are incapable to secure the IV data sharing against malicious attacks. Blockchain, as expected by both research and industry communities, has emerged as a good solution to address these issues. The major issues in IV data sharing are trust, data accuracy and reliability of data sharing in the communication channel. Blockchain technology, previously working for the cryptocurrency, has recently applied to build trust and reliability in peer-to-peer networks with similar topologies of IV data sharing. In this chapter, we present a new framework, namely biometric blockchain (BBC), for secure IV data sharing. In our new scheme, biometric information is exploited as a cue to record who is responsible in the data sharing activities, while the proposed BBC technology serves as the backbone of the IV data-sharing architecture. Hence, the proposed BBC technology provides a more reliable trust environment between the vehicles while personal identities are traceable in the proposed new scheme.
Jun Zhao, Jing Tang, Zengxiang Li, Huaxiong Wang · 6 authors
Formal analyses of blockchain protocols have received much attention recently. Consistency results of Nakamoto's blockchain protocol are often expressed in a quantity $c$, which denotes the expected number of network delays before some block is mined. With $μ$ (resp., $ν$) denoting the fraction of computational power controlled by benign miners (resp., the adversary), where $μ+ ν= 1$, we prove for the first time that to ensure the consistency property of Nakamoto's blockchain protocol in an asynchronous network, it suffices to have $c$ to be just slightly greater than $\frac{2μ}{\ln (μ/ν)}$. Such a result is both neater and stronger than existing ones. In the proof, we formulate novel Markov chains which characterize the numbers of mined blocks in different rounds.
Zhimin Gao, Lei Xu, Keshav Kasichainula, Lin Chen · 6 authors
Bitcoin brings a new type of digital currency that does not rely on a central system to maintain transactions. By benefiting from the concept of decentralized ledger, users who do not know or trust each other can still conduct transactions in a peer-to-peer manner. Inspired by Bitcoin, other cryptocurrencies were invented in recent years such as Ethereum, Dash, Zcash, Monero, Grin, etc. Some of these focus on enhancing privacy for instance crypto note or systems that apply the similar concept of encrypted notes used for transactions to enhance privacy (e.g., Zcash, Monero). However, there are few mechanisms to support the exchange of privacy-enhanced notes or assets on the chain, and at the same time preserving the privacy of the exchange operations. Existing approaches for fair exchanges of assets with privacy mostly rely on off-chain/side-chain, escrow or centralized services. Thus, we propose a solution that supports oblivious and privacy-protected fair exchange of crypto notes or privacy enhanced crypto assets. The technology is demonstrated by extending zero-knowledge based crypto notes. To address "privacy" and "multi-currency", we build a new zero-knowledge proving system and extend note format with new property to represent various types of tokenized assets or cryptocurrencies. By extending the payment protocol, exchange operations are realized through privacy enhanced transactions (e.g., shielded transactions). Based on the possible scenarios during the exchange operation, we add new constraints and conditions to the zero-knowledge proving system used for validating transactions publicly.
Saraju P. Mohanty, Venkata P. Yanambaka, Elias Kougianos, Deepak Puthal
This article presents the first-ever blockchain which can simultaneously handle device and data security, which is important for the emerging Internet-of-Everything (IoE). This article presents a unique concept of blockchain that integrates hardware security primitives called Physical Unclonable Functions (PUFs) to solve scalability, latency, and energy requirement challenges and is called PUFchain. Data management and security (and privacy) of data, devices, and individuals, are some of the issues in the IoE architectures that need to be resolved. Integrating the blockchain into the IoE environment can help solve these issues and helps in the aspects of data storage and security. This article introduces a new blockchain architecture called PUFchain and introduces a new consensus algorithm called "Proof of PUF-Enabled Authentication" (PoP) for deployment in PUFchain. The proposed PoP is the PUF integration into our previously proposed Proof-of-Authentication (PoAh) consensus algorithm and can be called "Hardware-Assisted Proof-of-Authentication (HA-PoAh)". However, PUF integration is possible in the existing and new consensus algorithms. PoP utilizes PUFs which are responsible for generating a unique key that cannot be cloned and hence provide the highest level of security. A PUF uses the nanoelectronic manufacturing variations that are introduced during the fabrication of an integrated circuit to generate the keys. Hence, once generated from a PUF module, the keys cannot be cloned or generated from any other module. PUFchain uses a PUF and Hashing module which performs the necessary cryptographic functions. Hence the mining process is offloaded to the hardware module which reduces the processing times. PoP is approximately 1,000X faster than the well-established Proof-of-Work (PoW) and 5X faster than Proof-of-Authentication (PoAh).
T Velmurugan, P. Prakasam, Noor Mohammed, K Saravanan
In city areas where people are more, managing garbage is in an inappropriate way leading to multiplying of germs that can cause illness. There is a difference in how frequently they use these litter bins in various regions. Periodic checking with timing gaps does not help. They may overflow at times even earlier than expected. To avoid this and to enhance the cleaning, a smart garbage monitoring method to find when the garbage can is full is proposed in this paper. The method’s design gathers such information as well as transmits it via a network of wireless type. In this proposed method, sensing of the dustbin’s trash level is done by sensors as well as information is transmitted to the official mobile station via GSM and GPS module. Online monitoring of the garbage level at control room is made using a WiFi Module. Arduino processor interfaces the system of sensors with the network modules. This data helps contracted cleaners as well as those who provide garbage cans, promptly empty to maintain the area spick and span..
Zhimin Gao, Lei Xu, Keshav Kasichainula, Lin Chen · 6 authors
Bitcoin brings a new type of digital currency that does not rely on a central\nsystem to maintain transactions. By benefiting from the concept of\ndecentralized ledger, users who do not know or trust each other can still\nconduct transactions in a peer-to-peer manner. Inspired by Bitcoin, other\ncryptocurrencies were invented in recent years such as Ethereum, Dash, Zcash,\nMonero, Grin, etc. Some of these focus on enhancing privacy for instance crypto\nnote or systems that apply the similar concept of encrypted notes used for\ntransactions to enhance privacy (e.g., Zcash, Monero). However, there are few\nmechanisms to support the exchange of privacy-enhanced notes or assets on the\nchain, and at the same time preserving the privacy of the exchange operations.\nExisting approaches for fair exchanges of assets with privacy mostly rely on\noff-chain/side-chain, escrow or centralized services. Thus, we propose a\nsolution that supports oblivious and privacy-protected fair exchange of crypto\nnotes or privacy enhanced crypto assets. The technology is demonstrated by\nextending zero-knowledge based crypto notes. To address "privacy" and\n"multi-currency", we build a new zero-knowledge proving system and extend note\nformat with new property to represent various types of tokenized assets or\ncryptocurrencies. By extending the payment protocol, exchange operations are\nrealized through privacy enhanced transactions (e.g., shielded transactions).\nBased on the possible scenarios during the exchange operation, we add new\nconstraints and conditions to the zero-knowledge proving system used for\nvalidating transactions publicly.\n
Shehu M. Sarkintudu, Huda Ibrahim, Alawiyah Abd Wahab
A number of previous articles obtained from the IS research databases and conferences on cryptocurrency platform emphasize on protocol and network layers which are more of the technical perspective. However, there are very few articles that focused on the practitioners as they can be a source of knowledge on the ecosystem layer of the platform Review
This paper presents TXSC, a framework that provides smart contract developers with transaction primitives. These primitives allow developers to write smart contracts without the need to reason about the anomalies that can arise due to concurrent smart contract function executions.
In this paper, we study forecasting problems of Bitcoin-realized volatility computed on data from the largest crypto exchange—Binance. Given the unique features of the crypto asset market, we find that conventional regression models exhibit strong model specification uncertainty. To circumvent this issue, we suggest using least squares model-averaging methods to model and forecast Bitcoin volatility. The empirical results demonstrate that least squares model-averaging methods in general outperform many other conventional regression models that ignore specification uncertainty.
Haijun Wang, Ye Liu, Yi Li, Shang‐Wei Lin · 7 authors
Despite the high stakes involved in smart contracts, they are often developed in an undisciplined manner, leaving the security and reliability of blockchain transactions at risk. In this article, we introduce ContraMaster—an oracle-supported dynamic exploit generation framework for smart contracts. Existing approaches mutate only single transactions; ContraMaster exceeds these by mutating the transaction sequences. ContraMaster uses data-flow, control-flow, and the dynamic contract state to guide its mutations. It then monitors the executions of target contract programs, and validates the results against a general-purpose semantic test oracle to discover vulnerabilities. Being a dynamic technique, it guarantees that each discovered vulnerability is a violation of the test oracle and is able to generate the attack script to exploit this vulnerability. In contrast to rule-based approaches, ContraMaster has not shown any false positives, and it easily generalizes to unknown types of vulnerabilities (e.g., logic errors). We evaluate ContraMaster on 218 vulnerable smart contracts. The experimental results confirm its practical applicability and advantages over the state-of-the-art techniques, and also reveal three new types of attacks.
Redhwan Al-Amri, Nur Haryani Zakaria, Adib Habbal, Suhaidi Hassan
In this research, a Systematic Literature Review (SLR) is performed to identify the carried-out research topics related to cryptocurrency adoption and models that have been used as well as the current adoption challenges that need to be overcome in future studies.
Maximilian Schiedermeier, Omar M. Hassan, Lionel Brunie, Tobias Mayer · 5 authors
High voter turnout in elections and referendums is very desirable in order to ensure a robust democracy. Secure electronic voting is a vision for the future of elections and referendums. Such a system can counteract factors that hinder strong voter turnout such as the requirement of physical presence during limited hours at polling stations. However, this vision brings transparency and confidentiality requirements that render the design of such solutions challenging. Specifically, the counting must be implemented in a reproducible way and the ballots of individual voters must remain concealed. In this paper, we propose and evaluate a referendum protocol that ensures transparency, confidentiality, and integrity, in trustless networks. The protocol is built by combining Secure Multi-Party Computation (SMPC) and Distributed Ledger or Blockchain technology. The persistence and immutability of the protocol communication allows verifiability of the referendum outcome on the client side. Voters therefore do not need to trust in third parties. We provide a formal description and conduct a thorough security evaluation of our proposal.
This paper proposes a random network model for blockchains, a distributed hierarchical data structure of blocks that has found several applications in various industries. The model is parametric on two probability distribution functions governing block production and communication delay, which are key to capture the complexity of the mechanism used to synchronize the many distributed local copies of a blockchain. The proposed model is equipped with simulation algorithms for both bounded and unbounded number of distributed copies of the blockchain. They are used to study fast blockchain systems, i.e., blockchains in which the average time of block production can match the average time of message broadcasting used for blockchain synchronization. In particular, the model and the algorithms are useful to understand efficiency criteria associated with fast blockchains for identifying, e.g., when increasing the block production will have negative impact on the stability of the distributed data structure given the network's broadcast delay.
Digital assets are hot right now. Whether cryptocurrencies, like bitcoin, or initial coin offerings and tokens, this new asset class has captured the imagination of American investors. While it remains to be seen if this phenomenon has staying power, there is no doubt that these assets and their promoters have attracted the attention of the Securities and Exchange Commission. But neither Congress nor the SEC has formally elucidated which digital assets are securities and which are not. This Article seeks to provide clarity in determining which digital assets are securities. It proposes two tests that operationalize the Supreme Court’s test in SEC v. W. J. Howey Co. The first test is the Bahamas Test, which asks whether a digital asset is sufficiently decentralized such that it is not a security. The second test is the Substantial Steps Test which is used to determine whether an investment is made with an expectation of profit. This Article takes a rules-based approach to provide clarity and begin a conversation about crafting more predictable jurisprudence and regulation in this area.