Raaj Anand Mishra, Anshuman Kalla, An Braeken, Madhusanka Liyanage
Internet of Things (IoT) has proved its applicability in numerous domains such as healthcare, agriculture, automobile, industrial production, logistics and supply chain management. Looking at the current trend, we expect massive proliferation of such IoT devices all around us. However, one of the issues with the widespread use of IoT is the increasing complexity of the underlying architecture, which lead to difficulty in ensuring security compliance. One of the critical security processes is key refreshment, which needs to be regularly executed in order to guarantee strong security management. However, in most of the cases, keys are not updated and if they are updated, the update-logs are not available for all the entities to verify and build trust. Furthermore, the rules for key refreshment are also not defined in a transparent way. In this paper, we propose secure, decentralized, and automatic key refreshment mechanism for an IoT system. The proposed mechanism enables users to verify the freshness of the security keys (being used) thereby relying on the data from IoT devices and establishing trust in an IoT system. The proposed mechanism is driven by blockchain technology and smart contract. To demonstrate the viability of the proposed solution we have implemented it using both Ethereum and Hyperledger Fabric blockchains.
As an investor, volatility plays an important role in decision making. It is defined as the rate at which a security’s price increases or decreases, i.e., shows pricing behavior during a definite span of time. A high volatility will lead to high risk. Thus, it becomes critical to determine the volatility and the risk-return trade-off among investments. This paper tries to document the volatility and risk-return trade-off of four prominent crypto-currencies (Bitcoin, Ethereum, Binance and Ripple), based on market-capitalization. For analysis, closing prices of cryptocurrencies has been accumulated through secondary method for 365 days, starting from 1st March 2022 and ending on 28th February 2023. Standard Deviation and Kurtosis, used together for volatility and risk assessment, documented that Bitcoin has the highest volatility and risk associated with expected returns. Regression, for assessing the impact of volatility in BTC price on others, derived that ETH has a strong, but not very strong, bivariate relationship with BTC, among all the pairs. Durbin Watson (DW) test concluded that there was no auto-correlation in the prices of crypto-currencies, i.e., previous day’s price does not play significant role in today’s price. For risk-return trade-off, Coefficient of Variation (CoV) has been applied. It determined that Ethereum has the highest ratio indicating its non-suitability to a conservative investor because of having the lowest returns as compared to risks involved; while Binance has the lowest Coefficient of Variation (CoV) depicting lower risk and maximum return among all.
The rapid digitization of healthcare records has led to the accumulation of vast amounts of sensitive patient data, stored across various systems and platforms. To ensure the secure and efficient exchange of Electronic Health Records (EHRs) among healthcare providers, researchers, and patients themselves, the concept of cross-chain interoperability within blockchain technology emerges as a promising solution. Nevertheless, existing blockchain platforms exhibit several limitations. In order to address the issue of non-interoperability, the suggested method involves creating a connection between two similar blockchain networks. This solution is exemplified through the use of an Electronic Health Records (EHR) structure, which is distributed across distinct Ethereum Testnets and implemented via a Solidity Smart Contract. The paper aims to demonstrate the viability of bridging the gap and fostering seamless interoperability between blockchain networks. However, establishing effective communication between these smart contracts proves to be a complex endeavor, whether within a singular blockchain or spanning multiple blockchains. This complexity presents a formidable obstacle, particularly when diverse hospitals require the sharing or exchange of critical information. Consequently, a solution becomes imperative to facilitate cross-chain communication among smart contracts. This solution provides seamless operation both within the confines of a single blockchain and across disparate blockchains. By achieving this, cross-chain interoperability can be realized, enabling distinct blockchain networks to mutually comprehend and actively engage with each other.
Polepaka Sanjeeva, M. Sai Sathwik, G. Sai Prasad, G. Praneeth Reddy · 6 authors
A decentralized and automated online voting system refers to an electronic voting method that leverages Blockchain technology to guarantee both transparency and security. It removes the need for intermediaries, making it more efficient and cost-effective than traditional voting methods. Aim of the paper is to develop an online voting system using Blockchain technology for secure and transparent voting. The proposed approach involves developing a decentralized voting system using Ethereum Blockchain technology. Smart contracts are used to manage the voting process and ensure its integrity. The datasets used in this paper will consist of mock voting data to simulate a real-world scenario. The results and discussions include an analysis of the system’s performance in terms of security, scalability, and usability. Future enhancements include integrating biometric authentication for enhanced security and accessibility.
Open access
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Internet of Vehicular Things (IoVT), as a subset of the Internet of Things (IoT), enhances safety, traffic management, and driver experience by connecting vehicles and facilitating data exchange. Indeed, the implementation of IoVT comes with its fair share of challenges, which include transparent and secure service management, security, privacy preservation, and prevention of malware attacks. Researchers have proposed reputation-based systems, including blockchain-supported ones, as effective solutions to address the challenges in IoVT, offering benefits such as integrity, authenticity, transparency, and privacy preservation support. On the other hand, cryptocurrency offers several advantages, such as decentralization, enhanced security, and lower transaction costs, making it an effective form of payment that can bypass traditional intermediaries and facilitate fast and borderless transactions with greater financial privacy and control for users. In this paper, a blockchain-based reputation management system is proposed that can collect information about the surroundings from intelligent vehicles, convert that data into appropriate information, and make necessary decisions regarding reported incidents. A cryptocurrency-based recovery system allows defaulters to recover their missing points through the use of digital tokens or assets, providing them with a transparent and decentralized mechanism for restoring their lost value or reputation. The proposed method for the cryptocurrency-based recovery system is implemented and tested using virtual machines, specifically utilizing the Ethereum blockchain and smart contract programming as proof of concept to showcase the functionality and feasibility of the system. Additionally, the packet structure and the throughput are also demonstrated to prove the efficiency of the proposed method.
Khaled Almiani, Young Choon Lee, Tawfiq Alrawashdeh, Amirmohammad Pasdar
The usage of blockchain technology has been significantly expanded with smart contracts and blockchainoracles. While smart contracts enables to automate the execution of an agreement between untrusted parties, oracles provide smart contracts with data external to a given blockchain, i.e., off-chain data. However, the validity and accuracy of such off-chain data can be questionable that compromises the transparency and immutability chacteristics of blockchain. Despite many studies on the trustworthiness of blockchain oracles, more precisely, off-chain data, their solutions are often ‘short-sighted’ and dependent on binary decisions. In this paper, we present a novel graph-based profiling method to determine the trustworthiness of blockchain oracles. We construct a graph with oracles as nodes and cumulative average discrepancies of validity and accuracy of data as edge weights. Our profiling method continues to update the graph, edge weights in particular, to distinguish trustworthy oracles. Clearly. this discourages the provision of false and inaccurate data. We have conducted an evaluation study to see the effectiveness of our proposed method, in which we have run the experiments utilizing the Ethereum network. Additionally, we have also calculated the cost of running these experiments. Consequently, our experiment results show that the proposed method achieves around 93% accuracy in identifying the trustworthiness of data sources.
The Covid-19 pandemic affected financial markets in several ways, influencing the dynamics of the relationships between asset classes. We investigate the connectedness between cryptocurrencies and international energy markets from 2018 to 2021 using the time-varying parameter vector autoregression approach. Net total directional connectedness suggests that the cryptocurrency and energy indexes had heterogeneous roles. Bitcoin and Ripple coin were the net receivers of shocks, while Ethereum switched from receiver to transmitter. The US energy market was a persistent net transmitter of shocks, while Asian energy markets were consistent net shock receivers. Pairwise connectedness reveals that cryptocurrencies can explain the volatility of the energy markets during the difficult period of the pandemic at the beginning of 2020. We provide insights for portfolio optimization and policy implications.
Fahad F. Alruwaili, Bayan Alabduallah, Hamed Alqahtani, Ahmed S. Salama · 6 authors
Blockchain (BC) and Artificial intelligence (AI) based technologies have earned a better reputation amongst the research community, especially in the medical field. BC technology has emerged as a promising solution to revolutionize the medical field by addressing challenges related to efficiency, data security, and interoperability. A BC-aided smart healthcare system leverages the immutable and decentralized nature of BC to construct a secured and transparent ecosystem to manage processes and healthcare data. It leverages the secure and decentralized nature of BC to optimize the processes, security, interoperability, and efficiency of medical data. The existing system is exposed to security attacks on healthcare data. It can be necessary to construct a real-time detection device utilizing a cyber-physical system (CPS) with BC technology in a significant way. This article designs a novel Blockchain-Enabled Smart Healthcare System using Jellyfish Search Optimization with Dual-Pathway Deep Convolutional Neural Network (JSO-DPCNN) technique. The presented JSO-DPDCNN technique exploits the concept of BC-enabled secure data transmission and DL-based diagnosis model for moneypox disease on smart healthcare monitoring. To accomplish this, the JSO-DPCNN technique uses Ethereum-based public BC to secure the privacy of healthcare images. In addition, the JSO-DPCNN technique applies a feature extraction module using DPCNN, which extracts the suitable set of features in the input images. Moreover, the multiplicative long short-term memory (MLSTM) approach was used for the disease detection process. Lastly, the JSO system can be employed for the parameter tuning of the MLSTM model. The simulation result of the JSO-DPCNN system was executed on a benchmark medical dataset. The comprehensive outcomes highlighted the significant outcome of the JSO-DPCNN approach in terms of different measures.
Md. Anisul Islam Mahmud, A. A. Talha Talukder, Arbiya Sultana, Kazi Iftesam Amin Bhuiyan · 7 authors
The growing popularity of online news has prompted concerns regarding (i) the socio-political influence over news dissemination, (ii) the waning freedom of news media, (iii) and a facile news evaluation process. A piece of news having the power to capture a large audience and sow the seed of bizarre consequences on a national scale should be prudently evaluated before reaching the mass. In quest of making a substantial profit, and sometimes due to inevitable socio-political influence, news with biased heading outpours mass media, resulting in ambiguity and mass manipulation. In this paper, we suggest a blockchain, smart contract, and incremental machine learning-based news evaluation procedure for the Bengali language to overcome these challenges. Weighted synthesis of machine classification and human expert opinion in a decentralized platform are synthesized to evaluate news. With continuous data, the Natural Language Processing (NLP) model is incrementally trained, and the best version of the model is used to detect deprived fake news. During experiments, the NLP model with initial training and testing accuracy of 84.94% and 84.99% was increased to 93.75% and 93.80% after nine rounds of incremental model training. On the Ethereum test network, the protocols have been installed and tested. The simulation demonstrates successful implementation of our proposed system.
Spyridon Georg Koustas, Max Jalowski, Tobias Reichenstein, Sascha Julian Oks
As manufacturing firms increasingly utilize IIoT technologies and sensor data is integrated into their processes, centralized architectures and the expansion of value creation networks pose challenges regarding data integrity and transparency. This offers an application context for the blockchain and smart contract technologies. Through a design science research approach a prototypical instantiation in form of a private Ethereum blockchain with RFID sensors as data inputs and ERC-721 tokens is created. The artifact is implemented into an industrial demonstrator, where the immutable tracking of workpieces during their production processes and the algorithm execution time are evaluated in trial runs.
Cryptocurrency has grown in popularity recently, and people try to get revenue from investing in cryptocurrency because the fluctuation is much larger than the stock market. However, because of this characteristic, some people lose a huge amount of money all of a sudden, or some people are addicted to it. Some experts claim that Nasdaq and Bitcoin exhibit a similar trend, showing a positive relationship between the two. Therefore, our research tries to prove that hypothesis with an artificial intelligence approach. The close price of the Nasdaq was used as an input variable, while the close price from Bitcoin and Ethereum was set as the target. Our experiment involves two different steps, which are EDA and machine learning analysis. For the first experiment, correlation matrix and joint plots were plotted, and Nasdaq and Bitcoin showed high correlation. Furthermore, six different machine learning algorithms and two deep learning algorithms were utilized for the analysis, and their accuracy was assessed with RMSE and MAE. RMSE and MAE of two coins based on Nasdaq were 1837.09 and 1066.32 for Bitcoin and 127 and 96.8 for Ethereum price prediction. However, even though the GRU yielded higher RMSE and MAE compared to the machine learning algorithm, visualization indicated that GRU was more effective than the machine learning model. Even though our research reveals a lower RMSE and MAE score compared to similar existing research, our finding is outstanding in that we proved that there exists a positive relationship between Nasdaq and Bitcoin.
Bitcoin and Ethereum are the top two cryptocurrencies in the first and the second places respectively. This study looks to examine the inter and intra dynamics and relationship between Bitcoin price (BTCP), Ethereum price (ETHP), Bitcoin volume (BTCV) and Ethereum volume (ETHV). This study utilizes the Johansen Cointegration Test as well as the Vector Error Correction Model (VECM) to determine the long-run relationship between Bitcoin price (BTCP), Ethereum price (ETHP), Bitcoin volume (BTCV) and Ethereum volume (ETHV) before and during the COVID-19 pandemic and to determine whether the pandemic has any effect on the changes in prices and volumes of these cryptocurrencies. The study also utilizes daily data extracted from coinmarketcap.com for Bitcoin price and volume as well as for Ethereum price and volume from August 8, 2015 up to February 28, 2021 extracted on March 1, 2021. We find that the COVID-19 pandemic has no effect on the long run relationship between Bitcoin price (BTCP), Ethereum price (ETHP), Bitcoin volume (BTCV) and Ethereum volume (ETHV) for all the specifications. We also find that the pandemic has no effect on the prices of Bitcoin and Ethereum but has an effect on their trading volumes in the short run. We find that the price of Bitcoin is positively related with the Bitcoin trading volume and positively related with the trading volume of Ethereum whereas the Ethereum price is negatively related with the Bitcoin trading volume and positively related with the trading volume of Ethereum. We also find that the price of Bitcoin is positively related with the trading volume of Bitcoin and negatively related with the trading volume of Ethereum. On the other hand, the price of Ethereum is positively related with trading volume of Bitcoin and positively related with the trading volume of Ethereum.
Kamal Addou, M. Y. El Ghoumari, S. Achkdir, Mohamed Azzouazi
Many food contamination incidents have occurred during the last decade which has proven the failure of the food supply chain management system to track the food, money, and information movement within the food supply chain. Many models have been established. This paper presents the design and implementation of the new model providing real-time data acquisition, monitoring, and storing on a tamper-proof blockchain of the main food supply movement. This system is using smart contracts that are deployed on the Ethereum blockchain to allow every participant to transact securely with other FSC players. IoT networks are implemented in different workplaces to gather multiple data about food status without human involvement to ensure transparency by different sensors. Machine learning models are established to ensure the correctness of the collected data and help drive decision making within the application or businesses.
Richard De Freitas Pinto, Viviane Fagundes de [UNESP] Mattos, Luiz Ricardo Nakamura
Esse trabalho apresenta a modelagem do volume mensal de transações da criptmoeda Ethereum por meio da metodologia de Box-Jenkins, envolvendo as etapas: análise exploratória, identificação, estimação e validação, algumas das quais executadas com a utilização de diferentes técnicas. O modelo encontrado pela modelagem SARIMA (Modelo autoregressivo integrado de médias móveis sazonal) conseguiu descrever o comportamento linear dos dados de forma satisfatória, mas não foi suficiente para descrever o comportamento da série, composta por movimento linear e não linear, sendo melhor representada por um modelo híbrido.
Blockchain is a technology that enables decentralized digital currencies like bitcoin, ethereum, and ripple. It is widely used in many areas such as healthcare, defense, and industrial domains like internet of things for tracking sensor data and detecting duplicate sensor data. Bitcoin is one of the most popular cryptocurrencies due to its market value and use as a medium of exchange. The trustless secure money exchanges have made bitcoins appealing to people. However, the loose possession of bitcoin keys can lead to monetary loss and a decrease in bitcoin users. In this article, we provide an extensive analysis of major privacy and security issues in the Bitcoin blockchain. First, we discuss the security issues in bitcoin, and second, we discuss countermeasures for these bitcoin threats. Third, we provide an added level of security using elliptic curve cryptography on bitcoin multi-signature accounts. Our research helps bitcoin users understand the risks involved in using non-multi-signature accounts compared to multi-signature accounts. The use of elliptic curve cryptography on bitcoin multi-signature accounts also helps to avoid unnecessary expenses such as bitcoin currency rewards to miners.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Diese Arbeit präsentiert ein Protokoll für vertrauliche Transaktionen auf Ethereum, das auf einer kontenbasierten Struktur und Paillier-Verschlüsselung basiert. Die Integration von Non-Interactive Zero-Knowledge Range Proofs (NIZKRP) verbessert die Sicherheit. Die Implementierung und Tests auf Ethereum zeigen vergleichbare Transaktionskosten (Sicherheitsparameter 40) im Vergleich zu Protokollen mit Bulletproofs. Bei einem Sicherheitsparameter von 128 (NIZKRP-Empfehlung) ist das Protokoll jedoch nicht anwendbar. Die Arbeit betont die Effizienz und Wettbewerbsfähigkeit, hebt jedoch die Herausforderung bei höheren Sicherheitsparametern hervor. Das Protokoll bildet eine solide Grundlage, erfordert jedoch weitere Optimierungen für breitere Anwendbarkeit.