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19 pages, 1569 KiB

Open AccessArticle

A Privacy-Preserving Authentication Scheme for a Blockchain-Based Energy Trading System

by Seunghwan Son, Jihyeon Oh, Deokkyu Kwon, Myeonghyun Kim, Kisung Park and Youngho Park

Mathematics 2023, 11(22), 4653; https://doi.org/10.3390/math11224653 - 15 Nov 2023

Cited by 2 | Viewed by 1575

Abstract

The adoption of renewable energies such as solar power, heat pumps, and wind power is on the rise, and individuals have started generating energy using their own solar panels. In recent years, many blockchain-based energy trading schemes have been proposed. However, existing schemes [...] Read more.

The adoption of renewable energies such as solar power, heat pumps, and wind power is on the rise, and individuals have started generating energy using their own solar panels. In recent years, many blockchain-based energy trading schemes have been proposed. However, existing schemes cannot fully address privacy issues and dependency on energy brokers during energy trading. In this paper, we propose a privacy-preserving authentication scheme for blockchain-based energy traders. An energy user encrypts a request message through lightweight attribute-based encryption, and only energy sellers who have proper attribute keys can decrypt and conduct further processes with the energy user. We analyze the proposed scheme using both informal and formal methods, such as the BAN logic, AVISPA simulation tool, and RoR model. Furthermore, we compare the computational and communication costs of our scheme with related schemes and show that the proposed scheme has competitive performance. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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22 pages, 7149 KiB

Open AccessArticle

Digital Authentication System in Avatar Using DID and SBT

by Geunyoung Kim and Jaecheol Ryou

Mathematics 2023, 11(20), 4387; https://doi.org/10.3390/math11204387 - 22 Oct 2023

Cited by 8 | Viewed by 2778

Abstract

Anonymity forms the basis of decentralized ecosystems, leading to an increase in criminal activities such as money laundering and illegal currency trading. Especially in blockchain-based metaverse services, activities such as preventing sexual crimes and verifying the identity of adults are becoming essential. Therefore, [...] Read more.

Anonymity forms the basis of decentralized ecosystems, leading to an increase in criminal activities such as money laundering and illegal currency trading. Especially in blockchain-based metaverse services, activities such as preventing sexual crimes and verifying the identity of adults are becoming essential. Therefore, avatar authentication and the KYC (Know Your Customer) process have become crucial elements. This paper proposes a mechanism to achieve the KYC process by verifying user identity using smart contracts. Users obtain an SBT (Soul Bound Token) from the metaverse service provider through the DID (Decentralized Identity) credential issued during the KYC process. The identity verification of avatars occurs within smart contracts, ensuring user privacy and protection through ZKP (Zero Knowledge Proof). Tools for generating ZKP are also provided, enabling users, even those who are unfamiliar with ZKP, to use them conveniently. Additionally, an integrated wallet is offered to seamlessly manage DID credentials and SBTs. Furthermore, in case of avatar identity issues, users can request an audit by the issuer through the associated DID tokens. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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23 pages, 917 KiB

Open AccessArticle

AI and Blockchain-Assisted Secure Data-Exchange Framework for Smart Home Systems

by Khush Shah, Nilesh Kumar Jadav, Sudeep Tanwar, Anupam Singh, Costel Pleșcan, Fayez Alqahtani and Amr Tolba

Mathematics 2023, 11(19), 4062; https://doi.org/10.3390/math11194062 - 25 Sep 2023

Cited by 5 | Viewed by 2630

Abstract

The rapid expansion of the Internet of Things (IoT) on a global scale has facilitated the convergence of revolutionary technologies such as artificial intelligence (AI), blockchain, and cloud computing. The integration of these technologies has paved the way for the development of intricate [...] Read more.

The rapid expansion of the Internet of Things (IoT) on a global scale has facilitated the convergence of revolutionary technologies such as artificial intelligence (AI), blockchain, and cloud computing. The integration of these technologies has paved the way for the development of intricate infrastructures, such as smart homes, smart cities, and smart industries, that are capable of delivering advanced solutions and enhancing human living standards. Nevertheless, IoT devices, while providing effective connectivity and convenience, often rely on traditional network interfaces that can be vulnerable to exploitation by adversaries. If not properly secured and updated, these legacy communication protocols and interfaces can expose potential vulnerabilities that attackers may exploit to gain unauthorized access, disrupt operations, or compromise sensitive data. To overcome the security challenges associated with smart home systems, we have devised a robust framework that leverages the capabilities of both AI and blockchain technology. The proposed framework employs a standard dataset for smart home systems, from which we first eliminated the anomalies using an isolation forest (IF) algorithm using random partitioning, path length, anomaly score calculation, and thresholding stages. Next, the dataset is utilized for training classification algorithms, such as K-nearest neighbors (KNN), support vector machine (SVM), linear discriminate analysis (LDA), and quadratic discriminant analysis (QDA) to classify the attack and non-attack data of the smart home system. Further, an interplanetary file system (IPFS) is utilized to store classified data (non-attack data) from classification algorithms to confront data-manipulation attacks. The IPFS acts as an onsite storage system, securely storing non-attack data, and its computed hash is forwarded to the blockchain’s immutable ledger. We evaluated the proposed framework with different performance parameters. These include training accuracy (99.53%) by the KNN classification algorithm and 99.27% by IF for anomaly detection. Further, we used the validation curve, lift curve, execution cost of blockchain transactions, and scalability (86.23%) to showcase the effectiveness of the proposed framework. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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29 pages, 1001 KiB

Open AccessArticle

NFT-Vehicle: A Blockchain-Based Tokenization Architecture to Register Transactions over a Vehicle’s Life Cycle

by Juan Carlos López-Pimentel, Luis Alberto Morales-Rosales, Ignacio Algredo-Badillo and Carolina Del-Valle-Soto

Mathematics 2023, 11(13), 2801; https://doi.org/10.3390/math11132801 - 21 Jun 2023

Cited by 4 | Viewed by 4435

Abstract

The sale of second-hand vehicles is a popular trade worldwide, and vehicle fraud is currently a common issue, mainly because buyers can lack a complete view of the historical transactions related to their new acquisition. This work presents a distributed architecture for stakeholders [...] Read more.

The sale of second-hand vehicles is a popular trade worldwide, and vehicle fraud is currently a common issue, mainly because buyers can lack a complete view of the historical transactions related to their new acquisition. This work presents a distributed architecture for stakeholders to register transactions over a vehicle’s life cycle in a blockchain network. The architecture involves a non-fungible token (NFT) linked to a physical motorized vehicle after a tokenization process, which denote as the NFT-Vehicle. The NFT-Vehicle is a hierarchical smart contract designed using an object-oriented paradigm and a modified version of the ERC721 standard. Every stakeholder engages with the NFT-Vehicle through distinct methods embedded within a smart contract. These methods represent internal protocols meticulously formulated and validated based on a finite-state machine (FSM) model. We implemented our design as a proof of concept using a platform based on Ethereum and a smart contract in the Solidity programming language. We carried out two types of proof: (a) validations, following the FSM model to ensure that the smart contract remained in a consistent state, and (b) proofs, to achieve certainty regarding the amount of ETH that could be spent in the life cycle of a vehicle. The results of the tests showed that the total transaction cost for each car throughout its life cycle did not represent an excessive cost considering the advantages that the system could offer to prevent fraud. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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31 pages, 407 KiB

Open AccessArticle

Balanced-DRL: A DQN-Based Job Allocation Algorithm in BaaS

by Chaopeng Guo, Ming Xu, Shengqiang Hu and Jie Song

Mathematics 2023, 11(12), 2638; https://doi.org/10.3390/math11122638 - 9 Jun 2023

Viewed by 1325

Abstract

Blockchain as a Service (BaaS) combines features of cloud computing and blockchain, making blockchain applications more convenient and promising. Although current BaaS platforms have been widely adopted by both industry and academia, concerns arise regarding their performance, especially in job allocation. Existing BaaS [...] Read more.

Blockchain as a Service (BaaS) combines features of cloud computing and blockchain, making blockchain applications more convenient and promising. Although current BaaS platforms have been widely adopted by both industry and academia, concerns arise regarding their performance, especially in job allocation. Existing BaaS job allocation strategies are simple and do not guarantee load balancing due to the dynamic nature and complexity of BaaS job execution. In this paper, we propose a deep reinforcement learning-based algorithm, Balanced-DRL, to learn an optimized allocation strategy in BaaS based on analyzing the execution process of BaaS jobs and a set of job scale characteristics. Following extensive experiments with generated job request workloads, the results show that Balanced-DRL significantly improves BaaS performance, achieving a 5% to 8% increase in job throughput and a 5% to 20% decrease in job latency. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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27 pages, 2647 KiB

Open AccessArticle

TRX Cryptocurrency Profit and Transaction Success Rate Prediction Using Whale Optimization-Based Ensemble Learning Framework

by Amogh Shukla, Tapan Kumar Das and Sanjiban Sekhar Roy

Mathematics 2023, 11(11), 2415; https://doi.org/10.3390/math11112415 - 23 May 2023

Cited by 3 | Viewed by 2669

Abstract

TRON is a decentralized digital platform that provides a reliable way to transact in cryptocurrencies within a decentralized ecosystem. Thanks to its success, TRON’s native token, TRX, has been widely adopted by a large audience. To facilitate easy management of digital assets with [...] Read more.

TRON is a decentralized digital platform that provides a reliable way to transact in cryptocurrencies within a decentralized ecosystem. Thanks to its success, TRON’s native token, TRX, has been widely adopted by a large audience. To facilitate easy management of digital assets with TRON Wallet, users can securely store and manage their digital assets with ease. Our goal is first to develop a methodology to predict the future price using regression and then move on to build an effective classifier to predict whether a profit or loss is made the next day and then make a prediction of the transaction success rate. Our framework is capable of predicting whether there will be a profit in the future based on price prediction and forecasting results using regressors such as XGBoost, LightGBM, and CatBoost with

R^{2}

values of 0.9820, 0.9825 and 0.9858, respectively. In this work, an ensemble-based stacking classifier with the Whale optimization approach has been proposed which achieves the highest accuracy of 89.05 percent to predict if there will be a profit or loss the next day and an accuracy of 98.88 percent of TRX transaction success rate prediction which is higher than accuracies obtained by standard machine learning models. An effective framework will be useful for better decision-making and management of risks in a cryptocurrency. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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26 pages, 4833 KiB

Open AccessArticle

Blockchain Transaction Fee Forecasting: A Comparison of Machine Learning Methods

by Conall Butler and Martin Crane

Mathematics 2023, 11(9), 2212; https://doi.org/10.3390/math11092212 - 8 May 2023

Cited by 3 | Viewed by 2698

Abstract

Gas is the transaction-fee metering system of the Ethereum network. Users of the network are required to select a gas price for submission with their transaction, creating a risk of overpaying or delayed/unprocessed transactions involved in this selection. In this work, we investigate [...] Read more.

Gas is the transaction-fee metering system of the Ethereum network. Users of the network are required to select a gas price for submission with their transaction, creating a risk of overpaying or delayed/unprocessed transactions involved in this selection. In this work, we investigate data in the aftermath of the London Hard Fork and shed insight into the transaction dynamics of the network after this major fork. As such, this paper provides an update on work previous to 2019 on the link between EthUSD/BitUSD and gas price. For forecasting, we compare a novel combination of machine learning methods such as Direct-Recursive Hybrid LSTM, CNN-LSTM, and Attention-LSTM. These are combined with wavelet threshold denoising and matrix profile data processing toward the forecasting of block minimum gas price, on a 5-min timescale, over multiple lookaheads. As the first application of the matrix profile being applied to gas price data and forecasting that we are aware of, this study demonstrates that matrix profile data can enhance attention-based models; however, given the hardware constraints, hybrid models outperformed attention and CNN-LSTM models. The wavelet coherence of inputs demonstrates correlation in multiple variables on a 1-day timescale, which is a deviation of base free from gas price. A Direct-Recursive Hybrid LSTM strategy is found to outperform other models, with an average RMSE of 26.08 and R² of 0.54 over a 50-min lookahead window compared to an RMSE of 26.78 and R² of 0.452 in the best-performing attention model. Hybrid models are shown to have favorable performance up to a 20-min lookahead with performance being comparable to attention models when forecasting 25–50-min ahead. Forecasts over a range of lookaheads allow users to make an informed decision on gas price selection and the optimal window to submit their transaction in without fear of their transaction being rejected. This, in turn, gives more detailed insight into gas price dynamics than existing recommenders, oracles and forecasting approaches, which provide simple heuristics or limited lookahead horizons. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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37 pages, 11799 KiB

Open AccessArticle

Invoice Discounting Using Kelly Criterion by Automated Market Makers-like Implementations

by Peplluis R. Esteva, Andrés El-Fakdi and Alberto Ballesteros-Rodríguez

Mathematics 2023, 11(7), 1673; https://doi.org/10.3390/math11071673 - 30 Mar 2023

Viewed by 2360

Abstract

Funding shortages are a persistent issue, particularly for small and medium-sized enterprises (SMEs), and the problem tends to worsen cyclically. The market for factoring and invoice discounting aims to address delays in payment for commercial invoices. These involves sellers present unpaid invoices to [...] Read more.

Funding shortages are a persistent issue, particularly for small and medium-sized enterprises (SMEs), and the problem tends to worsen cyclically. The market for factoring and invoice discounting aims to address delays in payment for commercial invoices. These involves sellers present unpaid invoices to financial organizations, typically banks, who provide an advance payment. The implementations of the factoring services without intermediaries in blockchain of the state of the art are all based on the publication on-chain of all the invoices, use know your customer (KYC) mechanisms, and over-collateralize the invoices. This article proposes a new, decentralized approach to lending services that completely eliminates intermediaries and does not require strong KYC, yet it is reasonably resilient. The approach uses liquidity pools and associated heuristics to create a model of risk compensation. In this model, a formula measures the contributed collateral to an invoice and the risk of a late invoice or non-payment, using the Kelly criterion to calculate the optimal premium for funding said invoice in the liquidity pool. The algorithm’s performance is tested in many scenarios involving several invoice amounts, collaterals, payment delays, and non-payment rates. The study also examines premium distribution policies and hack scenarios involving bogus, non-payable invoices. The outcome is a decentralized market that uses the Kelly criterion and is reasonably resilient to a wide range of invoicing scenarios, including 5% non-payment rates and 10% bogus invoices, yet provides a sound profit to liquidity providers. The algorithm’s resilience is enhanced by several premium distribution policies over partially collateralized invoices from 50 to 70%, resulting in optimal premium withdrawal policies every 30 days, making it the first protocol for loanable funds that does not require over-collateralization to be profitable and resilient. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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10 pages, 475 KiB

Open AccessArticle

Secure Access Control to Data in Off-Chain Storage in Blockchain-Based Consent Systems

by Mongetro Goint, Cyrille Bertelle and Claude Duvallet

Mathematics 2023, 11(7), 1592; https://doi.org/10.3390/math11071592 - 25 Mar 2023

Cited by 4 | Viewed by 3465

Abstract

Data access control is a crucial aspect of data management. Actors who want to share data need systems to manage consent in order to decide who can access their data. This guarantees the privacy of data, which is often sensitive. As a secure [...] Read more.

Data access control is a crucial aspect of data management. Actors who want to share data need systems to manage consent in order to decide who can access their data. This guarantees the privacy of data, which is often sensitive. As a secure distributed ledger, the blockchain is widely used today to manage consent for data access. However, a blockchain is not ideal for storing large volumes of data due to its characteristics. Therefore, it is often coupled with off-chain systems to facilitate the storage of these kinds of data. Therefore, data located outside the blockchain require security procedures. This article proposes a securing mechanism based on data encryption to secure data in off-chain storage in blockchain-based consent systems. The protocol uses a symmetric key system, which prevents the reading of data stored outside the sphere of the blockchain by malicious actors who would have access. The mechanism’s set up allows each set of data to be encrypted with a symmetric key that is anchored in a blockchain. This key is then used by the actors who have obtained the consent of the data owner to access and read the data stored outside the blockchain. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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12 pages, 258 KiB

Open AccessArticle

A New Code Based Signature Scheme for Blockchain Technology

by Adel Alahmadi, Selda Çalkavur, Patrick Solé, Abdul Nadim Khan, Mohd Arif Raza and Vaneet Aggarwal

Mathematics 2023, 11(5), 1177; https://doi.org/10.3390/math11051177 - 27 Feb 2023

Cited by 2 | Viewed by 2285

Abstract

Blockchain is a method of recording information that makes it not feasible for the system to be replaced, attacked, or manipulated. A blockchain is equipped with a notebook that copies and processes the various procedures across the network of computers participating in the [...] Read more.

Blockchain is a method of recording information that makes it not feasible for the system to be replaced, attacked, or manipulated. A blockchain is equipped with a notebook that copies and processes the various procedures across the network of computers participating in the blockchain. Digital signature algorithm is one of the cryptographic protocols used by the blockchain. In this work, we introduce a new digital signature scheme based on error correcting codes. In the scheme constructed on a [n, k, d]− code over

𝔽_{q}

, which is d ≥ 2t + 1, and the size of the signature length is n − k. The signature verification is based on the bounded distance decoding of the code. Since the verification space is

{𝔽_{q}}^{n}

, the proposed scheme has an improved performance in terms of working in a wider space. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

25 pages, 5352 KiB

Open AccessArticle

Clustering and Modelling of the Top 30 Cryptocurrency Prices Using Dynamic Time Warping and Machine Learning Methods

by Tomáš Šťastný, Jiří Koudelka, Diana Bílková and Luboš Marek

Mathematics 2022, 10(19), 3672; https://doi.org/10.3390/math10193672 - 7 Oct 2022

Cited by 6 | Viewed by 3216

Abstract

Cryptocurrencies are a new field of investment opportunities that has experienced a significant growth in the last decade. The crypto market was capitalized at more than USD 3000 bn, having grown from USD 10 m over the period 2011–2021. Generating high returns, investments [...] Read more.

Cryptocurrencies are a new field of investment opportunities that has experienced a significant growth in the last decade. The crypto market was capitalized at more than USD 3000 bn, having grown from USD 10 m over the period 2011–2021. Generating high returns, investments in cryptocurrencies have also shown high levels of price volatility. By comparing the performance of cryptocurrencies (measured by the crypto index) and standard equities (included in the S&P 500 index), we found that the former has outperformed the latter 14 times over the last two years. In the present paper, we analyzed the 2012–2022 global crypto market developments and main constituents. With a focus on the top 30 cryptocurrencies and their prices, as of 9 April 2022, covering data of the two major market stress events—outbreaks of the COVID-19 pandemic (February 2020) and the Russian invasion of Ukraine (February 2022). We applied the dynamic time warping method including barycentre averaging and k-Shape clustering of time series. The use of the dynamic time warping has been essential for the preparation of data for subsequent clustering and forecasting. In addition, we compared performance of cryptocurrencies and equities. Cryptocurrency time series are rather short, sometimes involving high levels of volatility and including multiple data gaps, whereas equity time series are much longer and well-established. Identifying similarities between them allows analysts to predict crypto prices by considering the evolution of similar equity instruments and their responses to historical events and stress periods. Moreover, we tested various forecasting methods on the 30 cryptocurrencies to compare traditional econometric methods with machine learning approaches. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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20 pages, 1177 KiB

Open AccessArticle

Neural Fairness Blockchain Protocol Using an Elliptic Curves Lottery

by Fabio Caldarola, Gianfranco d’Atri and Enrico Zanardo

Mathematics 2022, 10(17), 3040; https://doi.org/10.3390/math10173040 - 23 Aug 2022

Cited by 11 | Viewed by 2096

Abstract

To protect participants’ confidentiality, blockchains can be outfitted with anonymization methods. Observations of the underlying network traffic can identify the author of a transaction request, although these mechanisms often only consider the abstraction layer of blockchains. Previous systems either give topological confidentiality that [...] Read more.

To protect participants’ confidentiality, blockchains can be outfitted with anonymization methods. Observations of the underlying network traffic can identify the author of a transaction request, although these mechanisms often only consider the abstraction layer of blockchains. Previous systems either give topological confidentiality that may be compromised by an attacker in control of a large number of nodes, or provide strong cryptographic confidentiality but are so inefficient as to be practically unusable. In addition, there is no flexible mechanism to swap confidentiality for efficiency in order to accommodate practical demands. We propose a novel approach, the neural fairness protocol, which is a blockchain-based distributed ledger secured using neural networks and machine learning algorithms, enabling permissionless participation in the process of transition validation while concurrently providing strong assurance about the correct functioning of the entire network. Using cryptography and a custom implementation of elliptic curves, the protocol is designed to ensure the confidentiality of each transaction phase and peer-to-peer data exchange. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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27 pages, 6509 KiB

Open AccessArticle

On Proof-of-Accuracy Consensus Protocols

by Fredy Andres Aponte-Novoa and Ricardo Villanueva-Polanco

Mathematics 2022, 10(14), 2504; https://doi.org/10.3390/math10142504 - 19 Jul 2022

Cited by 4 | Viewed by 2681

Abstract

Consensus protocols are a fundamental part of any blockchain; although several protocols have been in operation for several years, they still have drawbacks. For instance, some may be susceptible to a 51% attack, also known as a majority attack, which may suppose a [...] Read more.

Consensus protocols are a fundamental part of any blockchain; although several protocols have been in operation for several years, they still have drawbacks. For instance, some may be susceptible to a 51% attack, also known as a majority attack, which may suppose a high risk to the trustworthiness of the blockchains. Although this attack is theoretically possible, executing it in practice is often regarded as arduous because of the premise that, with sufficiently active members, it is not ’straightforward’ to have much computing power. Since it represents a possible vulnerability, the community has made efforts to solve this and other blockchain problems, which has resulted in the birth of alternative consensus protocols, e.g., the proof of accuracy protocol. This paper presents a detailed proposal of a proof-of-accuracy protocol. It aims to democratize the miners’ participation within a blockchain, control the miners’ computing power, and mitigate the majority attacks. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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27 pages, 692 KiB

Open AccessArticle

Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle

by Nicolás Magner and Nicolás Hardy

Mathematics 2022, 10(13), 2338; https://doi.org/10.3390/math10132338 - 4 Jul 2022

Cited by 2 | Viewed by 3696

Abstract

This paper tests the random walk hypothesis in the cryptocurrency market. Based on the well-known Meese–Rogoff puzzle, we evaluate whether cryptocurrency returns are predictable or not. For this purpose, we conduct in-sample and out-of-sample analyses to examine the forecasting power of our model [...] Read more.

This paper tests the random walk hypothesis in the cryptocurrency market. Based on the well-known Meese–Rogoff puzzle, we evaluate whether cryptocurrency returns are predictable or not. For this purpose, we conduct in-sample and out-of-sample analyses to examine the forecasting power of our model built with autoregressive components and lagged returns of BITCOIN, compared with the random walk benchmark. To this end, we considered the 13 major cryptocurrencies between 2018 and 2022. Our results indicate that our models significantly outperform the random walk benchmark. In particular, cryptocurrencies tend to be far more persistent than regular exchange rates, and BITCOIN (BTC) seems to improve the predictive accuracy of our models for some cryptocurrencies. Furthermore, while the predictive performance is time varying, we find predictive ability in different regimes before and during the pandemic crisis. We think that these results are helpful to policymakers and investors because they open a new perspective on cryptocurrency investing strategies and regulations to improve financial stability. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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17 pages, 1451 KiB

Open AccessArticle

Delegated Proof of Accessibility (DPoAC): A Novel Consensus Protocol for Blockchain Systems

by Manpreet Kaur, Shikha Gupta, Deepak Kumar, Chaman Verma, Bogdan-Constantin Neagu and Maria Simona Raboaca

Mathematics 2022, 10(13), 2336; https://doi.org/10.3390/math10132336 - 3 Jul 2022

Cited by 20 | Viewed by 2589

Abstract

As the backbone of every blockchain application, the consensus protocol is impacted by numerous risks, namely resource requirements and energy consumption, which limit the usage of blockchain. Applications such as IoT/IIoT cannot use these high-cost consensus methods due to limited resources. Therefore, we [...] Read more.

As the backbone of every blockchain application, the consensus protocol is impacted by numerous risks, namely resource requirements and energy consumption, which limit the usage of blockchain. Applications such as IoT/IIoT cannot use these high-cost consensus methods due to limited resources. Therefore, we introduce Delegated Proof of Accessibility (DPoAC), a new consensus technique that employs secret sharing, PoS with random selection, and an interplanetary file system (IPFS).DPoAC is decomposed into two stages. During the initial stage, a secret is generated by a randomly chosen super node and divided into n shares. These shares are encrypted and stored in different n nodes on the IPFS network. The nodes will compete to access these shareholders to reconstruct the secret. The winning node will be awarded block generation rights. PoS with random selection is used in the second stage to compute the appropriate hash value and construct a block with valid transactions. In this novel approach, a node with few computational resources and small stakes can still obtain block generation rights by providing access to secret shares and reconstructing the secret, making the system reasonably fair. We qualitatively analyze and compare our scheme based on performance parameters against existing mainstream consensus protocols in the context of IoT/IIoT networks. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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21 pages, 1316 KiB

Open AccessArticle

Reminisce: Blockchain Private Key Generation and Recovery Using Distinctive Pictures-Based Personal Memory

by Jungwon Seo, Deokyoon Ko, Suntae Kim, Vijayan Sugumaran and Sooyong Park

Mathematics 2022, 10(12), 2047; https://doi.org/10.3390/math10122047 - 13 Jun 2022

Cited by 1 | Viewed by 4772

Abstract

As a future game-changer in various industries, cryptocurrency is attracting people’s attention. Cryptocurrency is issued on blockchain and managed through a blockchain wallet application. The blockchain wallet manages user’s digital assets and authenticates a blockchain user by checking the possession of a user’s [...] Read more.

As a future game-changer in various industries, cryptocurrency is attracting people’s attention. Cryptocurrency is issued on blockchain and managed through a blockchain wallet application. The blockchain wallet manages user’s digital assets and authenticates a blockchain user by checking the possession of a user’s private key. The mnemonic code technique represents the most widely used method of generating and recovering a private key in blockchain wallet applications. However, the mnemonic code technique does not consider usability to generate and recover a user’s private key. In this study, we propose a novel approach for private key generation and recovery. Our approach is based on the idea that a user can hold long-term memory from distinctive pictures. The user can generate a private key by providing pictures and the location of the pictures. For recovering a private key, the user identifies the locations of the pictures that are used in the private key generation process. In this paper, we experiment with the security and usability of our approach and confirm that our proposed approach is sufficiently secure compared to the mnemonic code technique and accounts for usability. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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18 pages, 568 KiB

Open AccessArticle

FORT: Right-Proving and Attribute-Blinding Self-Sovereign Authentication

by Xavier Salleras, Sergi Rovira and Vanesa Daza

Mathematics 2022, 10(4), 617; https://doi.org/10.3390/math10040617 - 17 Feb 2022

Cited by 5 | Viewed by 2584

Abstract

Nowadays, there are a plethora of services that are provided and paid for online, such as video streaming subscriptions, car-share, vehicle parking, purchasing tickets for events, etc. Online services usually issue tokens that are directly related to the identities of their users after [...] Read more.

Nowadays, there are a plethora of services that are provided and paid for online, such as video streaming subscriptions, car-share, vehicle parking, purchasing tickets for events, etc. Online services usually issue tokens that are directly related to the identities of their users after they sign up to a platform; users need to authenticate themselves by using the same credentials each time they use the service. Likewise, when using in-person services, such as going to a concert, after paying for this service, the user usually receives a ticket, which proves that he/she has the right to use that service. In both scenarios, the main concerns surround the centralization of these systems and that they do not ensure customers’ privacy. The involved service providers are trusted third parties—authorities that offer services and handle private data about users. In this paper, we designed and implemented FORT, a decentralized system that allows customers to prove their rights to use specific services (either online or in-person) without revealing sensitive information. To achieve decentralization, we proposed a solution where all of the data are handled by a blockchain. We describe and uniquely identify users’ rights using non-fungible tokens (NFTs), and possession of these rights is demonstrated by using zero-knowledge proofs—cryptographic primitives that allow us to guarantee customers’ privacy. Furthermore, we provide benchmarks of FORT, which show that our protocol is efficient enough to be used in devices with low computing resources, such as smartphones or smartwatches, which are devices commonly used in our use case scenario. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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17 pages, 1678 KiB

Open AccessArticle

BCmECC: A Lightweight Blockchain-Based Authentication and Key Agreement Protocol for Internet of Things

by Jan Lansky, Amir Masoud Rahmani, Saqib Ali, Nasour Bagheri, Masoumeh Safkhani, Omed Hassan Ahmed and Mehdi Hosseinzadeh

Mathematics 2021, 9(24), 3241; https://doi.org/10.3390/math9243241 - 14 Dec 2021

Cited by 10 | Viewed by 2883

Abstract

In this paper, targeting efficient authentication and key agreement in an IoT environment, we propose an Elliptic Curve Cryptography-(ECC) based lightweight authentication protocol called BCmECC which relies on a public blockchain to validate the users’ public key to provide desired security. We evaluate [...] Read more.

In this paper, targeting efficient authentication and key agreement in an IoT environment, we propose an Elliptic Curve Cryptography-(ECC) based lightweight authentication protocol called BCmECC which relies on a public blockchain to validate the users’ public key to provide desired security. We evaluate the security of the proposed protocol heuristically and validate it formally, which demonstratse the high level of the security. For the formal verification we used the widely accepted formal methods, i.e., BAN logic and the Scyther tool. In this paper we also analyse the security of recently proposed blockchain-based authentication protocols and show that this protocol does not provide the desired security against known session-specific temporary information attacks in which the adversary has access to the session’s ephemeral values and aims to retrieve the shared session key. In addition, the protocol lacks forward secrecy, in which an adversary with access to the server’s long-term secret key can retrieve the previous session keys, assuming that the adversary has already eavesdropped the transferred messages over a public channel in the target session. The proposed attacks are very efficient and their success probability is ‘1’, while the time complexity of each attack could be negligible. Besides, we show that BCmECC is secure against such attacks. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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19 pages, 2331 KiB

Open AccessArticle

A Novel Auction Blockchain System with Price Recommendation and Trusted Execution Environment

by Dong-Her Shih, Ting-Wei Wu, Ming-Hung Shih, Wei-Cheng Tsai and David C. Yen

Mathematics 2021, 9(24), 3214; https://doi.org/10.3390/math9243214 - 13 Dec 2021

Cited by 2 | Viewed by 3073

Abstract

Online auctions are now widely used, with all the convenience and efficiency brought by internet technology. Despite the advantages over traditional auction methods, some challenges still remain in online auctions. According to the World Business Environment Survey (WBES) conducted by the World Bank, [...] Read more.

Online auctions are now widely used, with all the convenience and efficiency brought by internet technology. Despite the advantages over traditional auction methods, some challenges still remain in online auctions. According to the World Business Environment Survey (WBES) conducted by the World Bank, about 60% of companies have admitted to bribery and manipulation of the auction results. In addition, buyers are prone to the winner’s curse in an online auction environment. Since the increase in information availability can reduce uncertainty, easy access to relevant auction information is essential for buyers to avoid the winner’s curse. In this study, we propose an Online Auction Price Suggestion System (OAPSS) to protect the data from being interfered with by third-party programs based on Intel’s Software Guard Extensions (SGX) technology and the characteristics of the blockchain. Our proposed system provides a smart contract by using α-Sutte indicator in the final transaction price prediction as a bidding price recommendation, which helps buyers to reduce the information uncertainty on the value of the product. The amount spent on the smart contract in this study, excluding deployed contracts, plus the rest of the fees is less than US$1. Experimental results of the simulation show that there is a significant difference (p < 0.05) between the recommended price group and the actual price group in the highest bid. Therefore, we may conclude that our proposed bidder’s price recommendation function in the smart contract may mitigate the loss of buyers caused by the winner’s curse. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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13 pages, 1028 KiB

Open AccessArticle

E-Learning Development Based on Internet of Things and Blockchain Technology during COVID-19 Pandemic

by Amir Masoud Rahmani, Rizwan Ali Naqvi, Mazhar Hussain Malik, Tauqeer Safdar Malik, Mahyar Sadrishojaei, Mehdi Hosseinzadeh and Ali Al-Musawi

Mathematics 2021, 9(24), 3151; https://doi.org/10.3390/math9243151 - 7 Dec 2021

Cited by 25 | Viewed by 3836

Abstract

The suspension of institutions around the world in early 2020 due to the COVID-19 virus did not stop the learning process. E-learning concepts and digital technologies enable students to learn from a safe distance while continuing their educational pursuits. Currently, the Internet of [...] Read more.

The suspension of institutions around the world in early 2020 due to the COVID-19 virus did not stop the learning process. E-learning concepts and digital technologies enable students to learn from a safe distance while continuing their educational pursuits. Currently, the Internet of Things (IoT) is one of the most rapidly increasing technologies in today’s digital world; and e-learning is one of the most powerful learning methods available. In today’s world, smart devices and new technologies assist teachers in concentrating on new models of student learning while avoiding time wastage. By examining the characteristics of the Internet of Things and the challenges that exist in the field of e-learning, the potential functions, benefits, and advancements of utilizing the Internet of Things in online education are identified and discussed. This article examines the existing and future condition of the Internet of Things world as it pertains to the topic of education and sophisticated capabilities available through the Internet of Things that enable the application of e-learning after an architecture has been designed. Students’ pulse rates, brain waves, and skin resistance are measured in real time by a collection of IoT sensors, including cameras, microphones, and wearable gadgets. By utilizing the proposed architecture, universities can change their distance learning tactics to maximize resources and boost efficiency without changing their overall academic activities. According to the study’s findings, e-learning has a favorable and statistically significant impact on students’ flexibility, learning experience, educational productivity, and overall quality of education. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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31 pages, 708 KiB

Open AccessArticle

Probability Models of Distributed Proof Generation for zk-SNARK-Based Blockchains

by Yuri Bespalov, Alberto Garoffolo, Lyudmila Kovalchuk, Hanna Nelasa and Roman Oliynykov

Mathematics 2021, 9(23), 3016; https://doi.org/10.3390/math9233016 - 24 Nov 2021

Cited by 8 | Viewed by 3396

Abstract

The paper is devoted to the investigation of the distributed proof generation process, which makes use of recursive zk-SNARKs. Such distributed proof generation, where recursive zk-SNARK-proofs are organized in perfect Mercle trees, was for the first time proposed in Latus consensus protocol for [...] Read more.

The paper is devoted to the investigation of the distributed proof generation process, which makes use of recursive zk-SNARKs. Such distributed proof generation, where recursive zk-SNARK-proofs are organized in perfect Mercle trees, was for the first time proposed in Latus consensus protocol for zk-SNARKs-based sidechains. We consider two models of a such proof generation process: the simplified one, where all proofs are independent (like one level of tree), and its natural generation, where proofs are organized in partially ordered set (poset), according to tree structure. Using discrete Markov chains for modeling of corresponding proof generation process, we obtained the recurrent formulas for the expectation and variance of the number of steps needed to generate a certain number of independent proofs by a given number of provers. We asymptotically represent the expectation as a function of the one variable n/m, where n is the number of provers m is the number of proofs (leaves of tree). Using results obtained, we give numerical recommendation about the number of transactions, which should be included in the current block, idepending on the network parameters, such as time slot duration, number of provers, time needed for proof generation, etc. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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22 pages, 326 KiB

Open AccessArticle

Motivations, Barriers and Risk-Taking When Investing in Cryptocurrencies

by Zdenek Smutny, Zdenek Sulc and Jan Lansky

Mathematics 2021, 9(14), 1655; https://doi.org/10.3390/math9141655 - 14 Jul 2021

Cited by 17 | Viewed by 8856

Abstract

The cryptocurrency market is very young, volatile, and highly risky. By the end of 2020, a new bull run started, and the prices of several cryptocurrencies reached record-breaking highs. The factors affecting this rise of cryptocurrencies include the impacts of the COVID-19 pandemic, [...] Read more.

The cryptocurrency market is very young, volatile, and highly risky. By the end of 2020, a new bull run started, and the prices of several cryptocurrencies reached record-breaking highs. The factors affecting this rise of cryptocurrencies include the impacts of the COVID-19 pandemic, the economic crisis and the global increase in the inflation rate, as well as the gradual acceptance and adoption of cryptocurrencies by people worldwide. This exploratory research is focused on this last factor, i.e., using cryptocurrency and with it, the associated support of its ecosystem (e.g., mining, staking). A survey was carried out investigating the motivational factors and barriers to investment in cryptocurrency for Czech representatives of Generations Y and Z (18–42 years; n = 468). The geographic scope was nationwide, and quota sampling was used. Notably, this survey was carried out prior to the global COVID-19 pandemic outbreak, and it is thus not affected by the pandemic and its related economic impacts. The article investigates the dependency between the individual motivational factors and barriers from the perspective of the tendency to take risks (using the risk propensity scale), according to gender and representation of Generations Y and Z. The lack of information on this form of investment is considered as the main barrier to investment in cryptocurrency, with respect to sex and generations. Compared to that, a negative experience with investment in cryptocurrency constitutes the most minor barrier. Respondents that have a tendency to take risks are mostly put off by their lack of experience with investment in general. The main motivational factor for investment in cryptocurrency, with respect to sex and generations, is considered to be the speed of increase in cryptocurrency value. On the other hand, the least encouraging factor is the opportunity to use the high volatility of cryptocurrency for speculative trading. Interestingly, this factor mostly encourages respondents that do not have a tendency to take risks. The findings are discussed, along with the presentation of their implications for practice and the directions of further explanatory research. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

23 pages, 624 KiB

Open AccessArticle

Analysis and Evaluation of Barriers Influencing Blockchain Implementation in Moroccan Sustainable Supply Chain Management: An Integrated IFAHP-DEMATEL Framework

by Omar Boutkhoum, Mohamed Hanine, Mohamed Nabil, Fatima El Barakaz, Ernesto Lee, Furqan Rustam and Imran Ashraf

Mathematics 2021, 9(14), 1601; https://doi.org/10.3390/math9141601 - 7 Jul 2021

Cited by 30 | Viewed by 5422

Abstract

Blockchain technology has received wide attention during recent years, and has huge potential to transform and improve supply chain management. However, its implementation in the SSCM (Sustainable Supply Chain Management) strategy is sophisticated, and the challenges are not explored very well, especially in [...] Read more.

Blockchain technology has received wide attention during recent years, and has huge potential to transform and improve supply chain management. However, its implementation in the SSCM (Sustainable Supply Chain Management) strategy is sophisticated, and the challenges are not explored very well, especially in the Moroccan context. To this end, the chief objective of the current endeavor is to investigate the barriers that hinder the adoption of blockchain technology in SSCM from the Moroccan industry and service sectors’ perspective. Based on a comprehensive literature search and the use of experts’ viewpoints, the barriers affecting the successful implementation of blockchain are classified into three categories called TEO: technological and system, environmental, and intra-organizational dimensions. In this context, a fuzzy group decision-making framework is organized by combining DEMATEL (Decision-Making Trial and Evaluation Laboratory) and IFAHP (Intuitionistic Fuzzy Analytic Hierarchy Process). The IFAHP technique helps to determine the importance/priorities of barriers affecting blockchain adoption, while the DEMATEL technique forms the cause–effect interconnections between these barriers and classifies them concerning the degree of importance and relationships. The results reveal that ‘government policy and support’ and ‘challenges in integrating sustainable practices and blockchain technology through SCM’ are significant adoption barriers of blockchain in Moroccan SSCM. The proposed solution can support industrial decision makers to form flexible short- and long-term decision-making strategies to efficiently manage a sustainable supply chain. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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Review

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21 pages, 954 KiB

Open AccessReview

Blockchain-Based Data Breach Detection: Approaches, Challenges, and Future Directions

by Kainat Ansar, Mansoor Ahmed, Markus Helfert and Jungsuk Kim

Mathematics 2024, 12(1), 107; https://doi.org/10.3390/math12010107 - 28 Dec 2023

Cited by 2 | Viewed by 2284

Abstract

In cybersecurity, personal data breaches have become one of the significant issues. This fact indicates that data breaches require unique detection systems, techniques, and solutions, which necessitate the potential to facilitate precise and quick data breach detection. Various research works on data breach [...] Read more.

In cybersecurity, personal data breaches have become one of the significant issues. This fact indicates that data breaches require unique detection systems, techniques, and solutions, which necessitate the potential to facilitate precise and quick data breach detection. Various research works on data breach detection and related areas in dealing with this problem have been proposed. Several survey studies have been conducted to comprehend insider data breaches better. However, these works did not examine techniques related to blockchain and innovative smart contract technologies to detect data breaches. In this survey, we examine blockchain-based data breach detection mechanisms developed so far to deal with data breach detection. We compare blockchain-based data breach detection techniques based on type, platform, smart contracts, consensus algorithm language/tool, and evaluation measures. We also present a taxonomy of contemporary data breach types. We conclude our study by outlining existing methodologies’ issues, offering ideas for overcoming those challenges, and pointing the way forward. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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29 pages, 639 KiB

Open AccessReview

A Review of the Key Technology in a Blockchain Building Decentralized Trust Platform

by Weichu Deng, Teng Huang and Haiyang Wang

Mathematics 2023, 11(1), 101; https://doi.org/10.3390/math11010101 - 26 Dec 2022

Cited by 15 | Viewed by 8134

Abstract

Currently, the trust mechanisms of various Internet application platforms are still built under the orders of centralized authorities. This centralized trust mechanism generally suffers from problems such as excessive power of central nodes, single point of failure and data privacy leakage. Blockchain is [...] Read more.

Currently, the trust mechanisms of various Internet application platforms are still built under the orders of centralized authorities. This centralized trust mechanism generally suffers from problems such as excessive power of central nodes, single point of failure and data privacy leakage. Blockchain is a new type of distributed data architecture with non-tamperability, openness and transparency, and traceability, which can achieve secure and trustworthy sharing of data without the participation of third-party authorities. The decentralized trust mechanism built based on the blockchain provides a new research paradigm with broad development prospects to solve the problem of establishing reliable information sharing under the environmental conditions of incomplete reliability in finance, healthcare, energy, and data security. In response to the issues exposed by centralized trust mechanisms in recent years, based on the critical technology of blockchain, this paper surveys the relevant literature around the vital issue of building a decentralized and secure trust mechanism. First, the decentralized trust mechanism architecture is sorted out by comparing different decentralized platforms. The blockchain is divided into the data layer, network layer, consensus layer, contract layer and application layer, which correspond to the theory, implementation, operation, extension, and application of the decentralized trust mechanism of a blockchain, a district-centric platform. Secondly, the principles and technologies of blockchain are elaborated in detail, focusing on the underlying principles, consensus algorithms, and smart contracts. Finally, blockchain problems and development directions are summarized in light of relevant literature. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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45 pages, 3417 KiB

Open AccessReview

Reinforcement Learning-Based Routing Protocols in Vehicular Ad Hoc Networks for Intelligent Transport System (ITS): A Survey

by Jan Lansky, Amir Masoud Rahmani and Mehdi Hosseinzadeh

Mathematics 2022, 10(24), 4673; https://doi.org/10.3390/math10244673 - 9 Dec 2022

Cited by 26 | Viewed by 3375

Abstract

Today, the use of safety solutions in Intelligent Transportation Systems (ITS) is a serious challenge because of novel progress in wireless technologies and the high number of road accidents. Vehicular ad hoc network (VANET) is a momentous element in this system because they [...] Read more.

Today, the use of safety solutions in Intelligent Transportation Systems (ITS) is a serious challenge because of novel progress in wireless technologies and the high number of road accidents. Vehicular ad hoc network (VANET) is a momentous element in this system because they can improve safety and efficiency in ITS. In this network, vehicles act as moving nodes and work with other nodes within their communication range. Due to high-dynamic vehicles and their different speeds in this network, links between vehicles are valid for a short time interval. Therefore, routing is a challenging work in these networks. Recently, reinforcement learning (RL) plays a significant role in developing routing algorithms for VANET. In this paper, we review reinforcement learning and its characteristics and study how to use this technique for creating routing protocols in VANETs. We propose a categorization of RL-based routing schemes in these networks. This paper helps researchers to understand how to design RL-based routing algorithms in VANET and improve the existing methods by understanding the challenges and opportunities in this area. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology)

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