D. N. Rao, G. Vidhya, M. Rajesh, Vipin Jain · 7 authors
The new IoT apps will not be able to inspire people to utilize them and may ultimately lose all their potential if an interoperable and trustworthy ecosystem is not provided. IoT has its extra security difficulties such as information storage, administration, privacy concerns, and authentication. The presently deployed IoT apps have encountered various security and privacy assaults globally. Due to being less secure and low powered, the IoT devices present a simple entryway to the adversaries to obtain access to the corporate networks, leading to giving easy control over all of the data of the users. The objective of this doctorate proposed work will be to solve the security associated difficulties in multiple IoT domains like the e‐commerce, vehicular ad hoc networks (VANET), mobile ad hoc networks (MANET), and Internet of Drones (IoD). The proposed study focuses on the development of a distributed framework for IoT based on blockchain. The framework includes the usage of Ethereum‐based smart contracts and auction models to increase the income and QoS for both the seller and the buyer and the development of a DAG chain‐based distributed framework for parking lot allocation in a network of automobiles. The suggested model includes the requirement of obtaining agreement among the nodes with probability one in such a circumstance. The suggested model demonstrates to be predictable as typical voting‐based consensus protocols like Practical Byzantine Fault Tolerance (PBFT) and at the same time can accommodate a high number of nodes even in an asynchronous setting. Research on Byzantine fault‐tolerant systems has been ongoing for more than four decades, and although the solutions were shown to be feasible early on, they remained unworkable for a long time. With PBFT, the first feasible solution was provided in 1999, and this sparked fresh research that has resulted in unique applications that are still being developed today employing this technology. Despite the fact that the safety and liveness properties of PBFT‐type protocols have been thoroughly investigated, when it comes to practical performance, only empirical results—often obtained in artificial environments—are known, and imperfections in the communication channels are not explicitly considered. It is our goal in this paper to propose the first performance model for PBFT that takes into account the effect of unreliable channels as well as the usage of alternative transport protocols across those channels. We also performed a large number of simulations to test the model and acquire a better understanding of the influence of different deployment factors on the total transaction timeframe.
A kriptovaluták piacának dinamikus fejlődésével párhuzamosan fontos pénzügyi és közgazdasági kérdések merülnek fel. A jelen kutatás fő fókusza a kriptovaluták árfolyamának alakulására irányul. A szakirodalmi bázis feltárása nyomán kiemelt figyelmet kapott a kriptopiac más eszközosztályok (arany, részvény, deviza) piacával való összehasonlítása, a kapcsolódási pontok azonosítása. Ezt követően a cikk a 2020 utáni időszakra fókuszálva, eseményelemzés (event study) segítségével igyekszik feltárni, hogy a két legnagyobb piaci kapitalizációval rendelkező kriptovaluta (a bitcoin és az ethereum) hogyan reagált néhány választott eseményre. Ez elsősorban a kriptovaluták működésének alapját képező rendszerek elleni hackertámadásokat jelenti, illetve a szabályozásukhoz, az alkalmazásukhoz kapcsolódó egyes lépéseket. Összességében megállapítottuk, hogy a hackertámadások nem hatottak szignifikánsan a két vizsgált kriptovaluta árfolyamára. A szabályozói lépések hatásai az árfolyamokra vegyesek, ám a szignifikáns hatások is rövid lefolyásúnak tekinthetők.
When Bitcoin became one of the world's most popular investment options, the cryptocurrency industry has showed potential development, and it had a similar influence on the Indian financial sector too. Aside from Bitcoin, other altcoins are gaining popularity and dominating the cryptocurrency market. As a result, the goal of this research is to identify at the macroeconomic factors that influence Bitcoin prices, such as the USD/INR exchange rate, gold prices, crude oil prices, the New York Stock Exchange Dow Jones (NYSE) price, NIFTY price, and Sensex price, as well as the prices of nine alternative cryptocurrencies in the cryptocurrency market: Binance coin, Bitcoin Cash, Bitcoin SV, Ether, Ethereum, Litecoin, Monero, Tether, and ripple. Bitcoin volume and market capitalization are additional factors, undertaken in the study, that are potential influencers of cryptocurrency pricing. The time series data, which comprises of bi-weekly data for all variables, will be used from 2015 to 2020. The OLS (ordinary least square) regression model in EVIEWS will be used in this study to conduct an empirical analysis.
Jan 1, 2022·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Hamza Sellak, Mohan Baruwal Chhetri, Zijin Huang, Marthie Grobler
Medical decision-making is moving away from the traditional one-off dyadic encounter between the patient and physician, and transitioning towards a more inclusive, shared decision-making process that also considers the inputs from other stakeholders. This ensures that a patient's decision is not only based on a medical opinion, but also includes other considerations such as impact on family members, legal and financial implications, and experiences of patients in similar situations. However, given the sensitive nature of health data and decisions, there are several challenges associated with safeguarding the privacy, security and consent of all contributors and assuring the integrity of the process. We propose a collaborative medical decision-making platform that uses a consensus building mechanism implemented using Blockchain-based Smart Contracts to address some of the above challenges, thereby giving the participants confidence that both the decision-making process and the outcome(s) can be trusted. We also present a proof-of-concept implementation using the private Ethereum Blockchain to demonstrate practicability.
This study uses the DCC-GARCH model to compare the correlation between two types of cryptocurrencies in two different fields.In the context of the popularity of NFTs and the metaverse, new cryptocurrencies based on the metaverse have been favored by investors.Through empirical analysis of mana cryptocurrencies in the NFT market, we find that the new cryptocurrencies in the NFT market have high volatility to Bitcoin, Ethereum, and traditional cryptocurrencies in the past year.Therefore, we conclude that new cryptocurrencies are more likely to be one of the factors for portfolio diversification.
Cryptocurrencies are deemed to be highly influenced and driven by investors' sentiments flowing across social media platforms. Consequently, researchers are attracted to investigate investors' behavioral biases in investing in cryptocurrencies. The existing related research majorly focuses on the investigation with the implementation of questionnaires and surveys. However, to what extent the feedbacks to these questionnaires or surveys truthfully reflect the investors' actual practices in investing in cryptocurrencies is uncertain and dubious. Therefore, in this study, we inspect and appraise the behavioral biases and portfolio properties of cryptocurrency investors by utilizing the on-blockchain (on-chain) information of wallet records directly from the Ethereum network. By retrieving and analyzing the unique wallet addresses and related transactions, we have obtained three behavioral bias proxies of the investors behind the wallets and five different properties of the wallets. Furthermore, we distinguish and analyze the wallets of human investors and trading bots. The results of statistical tests indicate the significant differences between human investors and trading bots on most behavioral biases and wallet properties.
This article proposes a power network management system based on blockchain technology to address the difficulties in distributed energy management in smart grids and power resource dispatching. Ethereum is used as the development platform to build a blockchain for power interaction management which mainly involves distributed energy transactions. In order to guarantee the rationality of energy transactions in the grid, this article presents a distributed power dispatching strategy using K-means clustering algorithm and particle swarm optimisation (PSO) algorithm. Finally, the distributed power matching transactions are completed in the power interaction management blockchain with the presence of power operation smart contracts. The experimental results show that the consensus mechanism and power dispatching strategy designed in this paper effectively solve the matching problem in distributed power trading. The application of the power operation smart contract further promotes the success rate of the transaction and effectively reduces its time consumption.
Md. Tayeen Khan, Md. Nozib Ud Dowla, Fardin Ahmed Niloy
The popularity of renewable energy is increasing due to its cost effectiveness. However, not everyone can generate and fulfill their energy demand, so energy trading is necessary. Current solutions are centralised and charged at a high fee for energy trading as they have a monopoly in the market. Energy trading requires the storage, verification, and sharing of data related to the trade while keeping records tamper-proof. Traditional database solutions are centralised and susceptible to data tempering. In our proposed scheme, we aim to solve those problems with the help of blockchain technology by storing data on blockchain and verifying transactions with the PoA consensus algorithm for faster processing. We tested our scheme against the Ethereum network and found that our scheme has a significant improvement in cost and processing. In the future, with the help of machine learning, pricing for each transaction can be optimised.
Wenjun Fan, Shubham Kumar, Sang‐Yoon Chang, Younghee Park
Abstract Collaborative intrusion detection approach uses the shared detection signature between the collaborative participants to facilitate coordinated defense. In the context of collaborative intrusion detection system (CIDS), however, there is no research focusing on the efficiency of the shared detection signature. The inefficient detection signature costs not only the IDS resource but also the process of the peer-to-peer (P2P) network. In this paper, we therefore propose a blockchain-based retribution mechanism, which aims to incentivize the participants to contribute to verifying the efficiency of the detection signature in terms of certain distributed consensus. We implement a prototype using Ethereum blockchain, which instantiates a token-based retribution mechanism and a smart contract-enabled voting-based distributed consensus. We conduct a number of experiments built on the prototype, and the experimental results demonstrate the effectiveness of the proposed approach.
In the world there no country, market or economy which is separated, and interconnection is becoming a fundamental feature of almost all social and economic systems. In the case of digital assets, such as cryptocurrencies, the impact of the relationship on their performance and price trajectory increases. The investigation of these phenomena is important for understanding the processes that govern cryptocurrencies. The objective of this paper is to assess the tightness of the relationship between the world's leading cryptocurrencies. In order to achieve this goal, the concepts of «cryptocurrency» and «blockchain», their history and features are considered. The principles of the first cryptocurrency – Bitcoin – are studied and the dynamics of changes in its price from 2015 to 2021 are analyzed. The price of Ethereum, XRP and major financial assets is compared. The best 20 cryptocurrencies at a certain time are identified with their price, capitalization and value changes over the last day and week. Based on the data from the Hackernoon website, research by Larry Chermak and the cryptocurrency publication The Block, it is determined that the strongest cryptocurrencies are interdependent or follow the most important cryptocurrency – bitcoin. Pearson's coefficient is considered. On its basis the correlation strength between eleven leading cryptocurrencies is determined, the part of the data are presented as a confidence interval. It is found that Ethereum and Litecoin have the strongest association with Bitcoin. Coin, Tron, Cardano, Bitcoin Cash, however, have low (negative) correlation between Tether or USDC. The main factors influencing the price of cryptocurrency are identified. It is also determined that alternative cryptocurrencies have lower correlation with bitcoin during periods of price growth, although the differences are not large, and during price decline the strength of bitcoin's correlation with other cryptocurrencies increases significantly, in most cases it reaches even very strong connection. The influence of social networks such as Google+ and Twitter on the price of cryptocurrency is determined as well. The proposed analysis makes it possible to understand the dynamics of cryptocurrency markets and the various processes that affect their efficiency.
Adeeba Naaz, T. V. Pavan Kumar B, Maria Francis, Kotaro Kataoka
Authentication while maintaining anonymity when availing a service over the internet is a significant privacy challenge. Anonymous credentials (AC) address this by providing the user with a credential issued by a trusted entity that convinces the service provider (SP) that the user is authenticated but reveals no other information. The existing AC schemes assume a single trusted authority (certifier) that validates all the user attributes. In practice, however, a user may require different attributes to be attested by different certifiers. This means that the user has to get multiple credentials, increasing the burden on theSPwho has to verify each one of them. Moreover, complete anonymity can be misused. We propose adecentralized threshold revocable anonymous credential (DTRAC)scheme over blockchains that supports – a) attestation of attributes by multiple certifiers, and b) anonymity revocation through a set of distributed openers, by integrating threshold opening to the state-of-the-art threshold anonymous credential issuance scheme, Coconut [34]. DTRAC generates a single credential on attributes that are attested by multiple certifiers, freeing the SP from the hassle of verifying multiple credentials. We analyze the security of DTRAC formally in the universal composability (UC) framework. We also implement a prototype on Ethereum using smart contracts and give a detailed analysis of its performance.We compare the verification time for credentials with attributes attested by multiple certifiers in both DTRAC and Coconut and see that in terms of execution time and gas consumption, DTRAC performs significantly better than Coconut. It also scales better, with the performance gain of DTRAC over Coconut increasing linearly with the number of certifiers.