Dian Gustina, I Gede Agus Suwartane, Yusuf Buditama
Intisari— Minting DApp NFT adalah proses pembuatan token non-fungible (NFT) di dalam aplikasi terdesentralisasi (DApp). NFT adalah aset digital unik yang dibuat menggunakan teknologi blockchain, yang menghasilkan keunikan dan kepemilikan yang terverifikasi. Pada dasarnya, proses minting DApp NFT melibatkan langkah- langkah berikut: Persiapan: Pengguna perlu mengakses DApp yang mendukung fungsi minting NFT. Biasanya, DApp ini berjalan di atas platform blockchain tertentu, seperti Ethereum atau Binance Smart Chain.Verifikasi Kepemilikan: Sebelum pengguna dapat melakukan minting, mereka harus terverifikasi sebagai pemilik aset digital yang ingin diubah menjadi NFT. Proses ini memastikan bahwa NFT yang dihasilkan berhubungan langsung dengan kepemilikan aset tersebut. Pembuatan Kontrak Cerdas: Dalam langkah ini, DApp akan berinteraksi dengan kontrak cerdas (smart contract) yang telah ditetapkan untuk menciptakan NFT. Kontrak cerdas ini berisi logika untuk mengelola pembuatan, pendaftaran, dan kepemilikan NFT. Proses Minting: Setelah persyaratan terpenuhi dan kontrak cerdas telah diberi perintah untuk menciptakan NFT, proses minting dimulai. Data aset digital yang mewakili NFT dienkripsi dalam bentuk token unik di blockchain. Penambahan Metadata: NFT biasanya menyertakan metadata yang memberikan informasi tambahan tentang aset digital, seperti judul, deskripsi, tanda tangan kreator, gambar, video, atau tautan yang relevan. Penambahan Ke Jaringan: Setelah NFT berhasil diciptakan dan metadata ditambahkan, NFT tersebut diunggah ke blockchain dan dapat diakses oleh siapa saja melalui alamat kontrak cerdas atau pasar NFT yang terhubung dengan DApp. Kepemilikan dan Transaksi: Setelah NFT dimiliki oleh seseorang, ia memiliki kendali penuh atas NFT tersebut. Mereka dapat memamerkan, menukar, menjual, atau mentransfer kepemilikannya dengan transaksi blockchain. Minting DApp NFT menawarkan cara yang transparan, terverifikasi, dan unik untuk menciptakan, memperoleh, dan memiliki aset digital di dunia maya. Hal ini telah memberikan kesempatan bagi seniman, kreator konten, dan kolektor untuk menciptakan, berpartisipasi dalam ekosistem NFT, serta memperluas pengalaman di ranah digital. Namun, karena NFT dan ekosistemnya masih dalam tahap perkembangan, penting bagi pengguna untuk tetap berhati-hati, melakukan riset, dan memahami aspek hukum dan keamanan sebelum berpartisipasi dalam aktivitas NFT. Kata Kunci : Non Fungible Token (NFT), Ethereum, Blockchain, Dapp, Cryptocurrency Abstract—Minting DApp NFT is the process of creating non-fungible tokens (NFTs) within a decentralized application (DApp). NFTs are unique digital assets created using blockchain technology, which provide uniqueness and verified ownership. Essentially, the process of minting DApp NFT involves the following steps Preparation: Users need to access a DApp that supports NFT minting functionality. Usually, these DApps run on a specific blockchain platform such as Ethereum or Binance Smart Chain. Ownership Verification: Before users can perform minting, they must be verified as the owners of the digital assets they want to transform into NFTs. This process ensures that the resulting NFT is directly associated with the ownership of the asset. Smart Contract Creation: In this step, the DApp will interact with a smart contract established to create NFTs. This smart contract contains logic to manage the creation, registration, and ownership of NFTs. Minting Process: Once the requirements are met, and the smart contract is instructed to create an NFT, the minting process begins. The data representing the NFT is encrypted in a unique token format on the blockchain. Metadata Addition: NFTs usually include metadata that provides additional information about the digital asset, such as title, description, creator's signature, image, video, or relevant links. Addition to the Network: After the NFT is successfully created, and metadata is added, the NFT is uploaded to the blockchain and can be accessed by anyone through the smart contract address or NFT marketplaces connected to the DApp. Ownership and Transactions: Once the NFT is owned by someone, they have full control over the NFT. They can showcase, trade, sell, or transfer ownership through blockchain transactions. Minting DApp NFT offers a transparent, verified, and unique way to create, acquire, and own digital assets in the virtual world. It has provided opportunities for artists, content creators, and collectors to participate in the NFT ecosystem and expand their experiences in the digital realm. However, as NFTs and their ecosystem are still in a developmental stage, it is crucial for users to remain cautious, conduct research, and understand legal and security aspects before engaging in NFT activities. Keyword— Non Fungible Token (NFT), Ethereum, Blockchain, Dapp, Cryptocurrency
<title>Abstract</title> Blockchain technology has gained significant attention in recent years due to its decentralized and secure nature. Ethereum a popular blockchain platform supports the execution of smart contracts and enables the storage of data on the blockchain. However Ethereum's public nature may not be suitable for scenarios where sensitive or private data needs to be stored and accessed securely. In this paper we present GANACHE an efficient private Ethereum blockchain tool that addresses the confidentiality and security concerns associated with data storage. GANACHE leverages various cryptographic techniques such as encryption and zero-knowledge proofs to ensure the privacy of stored data while maintaining the benefits of blockchain technology.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Bitcoin is always interesting to keep predicting where the next price movement will go. Bitcoin is the first and most influential Cryptocurrency on cryptocurrency price movements. Bitcoin is traded in many markets, the largest in Indonesia is Indodax. Indodax provides a document sharing API so that third parties can build applications that are able to process data on bitcoin price movements in real-time and continuously. This research shows how patterned datasets can be applied to monitor bitcoin price movements from the indodax market and show their effects on other cryptocurrency assets besides bitcoin. This research shows how data that is patterned and then processed using the minimum and maximum functions can provide 2 important information, namely the potential position of bitcoin when it is at the maximum and minimum points. The results of the patterned dataset formula are then compared to the movements of the 2 cryptocurrencies with the largest capitalization, namely BTC (Bitcoin) and ETH (Ethereum). The results of the comparison show that the use of patterned dataset formulas successfully shows important points in cryptocurrency trading, with simpler instructions.
Data in healthcare domain is highly sensitive in nature. Besides, there is need for maintaining integrity of such data. Blockchain technology has emerged to solve the problem of data integrity and non-repudiation with immutable storage in distributed repository. Thus secure data storage and retrieval in cloud environments is made possible using blockchain implementation. There are many existing healthcare systems with blockchain integration found in the literature. However, there is need for a system that supports complete set of operations that are governed by smart contracts. Another important consideration is that end users should be able to operate healthcare system without the need for knowledge of blockchain technology. Towards this end, in this paper, we proposed a Blockchain based secure healthcare data storage and retrieval system known as HealthBlock for cloud computing environments. We defined smart contract with underlying structures and functions using Solidity language for Ethereum blockchain platform. We also proposed and implemented an algorithm known as Healthcare Transactions over Blockchain (HToB). This algorithm supports secure blockchain based data storage and retrieval governed by smart contracts. Our system is evaluated using user-friendly web based client application. The experimental results showed that our system is able to ensure data integrity and non-repudiation besides reaping all benefits of blockchain technology.
This study aims to evaluate the impact of cryptocurrency regulations on human rights, with a particular focus on digital rights, privacy, and security. Cryptocurrencies, such as Bitcoin and Ethereum, have rapidly evolved as a new form of decentralized digital finance. However, this growth has raised questions about how cryptocurrencies affect individuals' rights, especially in terms of privacy and the security of personal data. This study employs a normative legal approach and conceptual analysis to explore existing regulations and trends related to cryptocurrency in various jurisdictions. Additionally, the research incorporates a theoretical perspective on human rights to identify potential implications of cryptocurrency regulation on privacy and digital security. The study's findings should shed light on how human rights are affected by the way cryptocurrencies are currently regulated and set the stage for any future legislative adjustments that would be required to strike a balance between personal safety and technological innovation. This research can also assist policymakers and regulators in tightening legal work practices, which will enable advancements in cryptocurrency while upholding individual rights. With the continuous growth in cryptocurrency usage and the growing concerns about privacy and security, this study is relevant in supporting ongoing discussions on how the law can accommodate this innovative technology without compromising human rights.
Dato Kavazi, Victor Smirnov, Sasha Shilina, Jonathan Shomroni · 7 authors
We present a novel 1 Human = 1 Node blockchain protocol which aims to overcome problems arising from plutocratic principles upon which Proof-of-Work (PoW) and Proof-of-Stake (PoS) heavily rely on. The advent of blockchain technology has led to a massive wave of different decentralized ledger technology (DLT) solutions. Projects such as Bitcoin and Ethereum managed to shift the paradigm of how to transact value in a decentralized manner, yet their core technologies give rise to a significant early adopters’ control bias and have led to financial systems flawed by massive inequality and centralization of power. In this paper we propose an alternative to modern decentralized financial networks by introducing the Humanode network. Humanode is a network safeguarded by cryptographically secure bio-authorized nodes on which users are able to deploy nodes by staking their encrypted biometric data. This approach can potentially lead to the creation of a truly public, permissionless financial network, based on consensus between equal human nodes with algorithmic emission mechanisms targeting real value growth and contribution-based wealth distribution.
Ibrahim Ramadan Abdelhamid, Islam Tharwat Abdel Halim, Ibrahim A. Ibrahim, Abd El-Majeed Amin Ali
This study explores the potential of blockchain technology to redefine public administration, focusing on the integration of Ethereum, a blockchain platform, and the Interplanetary File System (IPFS) for notarial certification issuance.The core aim is to evaluate the capacity of this technology to augment governmental efficacy, ensure transparency in service provision, decentralize data management, and maintain information integrity.The architectural components of the system comprise Ethereum's smart contracts, Ether, gas, and a decentralized application, supplemented by IPFS as a decentralized file storage system for a secure and transparent certificate issuance mechanism.Scalability assessments indicated efficient processing of multiple transactions per second (TPS), suggesting the system's capability to service a considerable number of simultaneous users.The encryption and decryption performance exhibited by IPFS, particularly for small content sizes of 250 KB and 500 KB, was near-instantaneous.Average times for deployment and execution were recorded as 9 seconds and 6 seconds, respectively.In conclusion, the synergistic integration of Ethereum and IPFS exhibits the potential to significantly transform public administration by augmenting efficiency and transparency in the delivery of citizencentric services.Notably, the incorporation of IPFS for secure file storage and hash transmissions was instrumental in optimizing cost-efficiency.
In recent years, blockchain technology has witnessed rapid development and received considerable attention. However, its decentralized and pseudonymous nature has also attracted many criminal activities. Among them, Ponzi schemes, a classic form of financial fraud, also hide their true face in smart contracts, causing huge losses to blockchain users. Although numerous methods have been proposed to detect Ponzi contracts, these methods still have limitations in terms of generalization and feature learning. To address this issue, we conduct research on Ethereum, the currently largest blockchain platform enabling smart contracts, and propose a novel contrastive learning-based smart Ponzi scheme detection method named ContraPonzi. This method first extracts control flow graph information from bytecodes and models it as attribute graphs that preserve both semantic and structural information. Next, by augmenting the bytecode data of multi-version compilers and maximizing the graph representation similarity of multi-version bytecodes of the same contract, a pre-training graph encoder is obtained and then can be used in Ponzi contract detection. Experimental results on real-world data demonstrate that ContraPonzi is significantly superior to the state-of-the-art in Ethereum Ponzi scheme detection.
Abstract Security threats posed by Ponzi schemes present a considerably higher risk compared to many other online crimes. These fraudulent online businesses, including Ponzi schemes, have witnessed rapid growth and emerged as major threats in societies like Nigeria, particularly due to the high poverty rate. Many individuals have fallen victim to these scams, resulting in significant financial losses. Despite efforts to detect Ponzi schemes using various methods, including machine learning (ML), current techniques still face challenges, such as deficient datasets, reliance on transaction records, and limited accuracy. To address the negative impact of Ponzi schemes, this paper proposes a novel approach focusing on detecting Ponzi schemes on Ethereum using ML algorithms like random forest (RF), neural network (NN), and K-nearest neighbor (KNN). Over 20,000 datasets related to Ethereum transaction networks were gathered from Kaggle and preprocessed for training the ML models. After evaluating and comparing the three models, RF demonstrated the best performance with an accuracy of 0.94, a class-score of 0.8833, and an overall-score of 0.96667. Comparative evaluations with previous models indicate that our model achieves high accuracy. Moreover, this innovative work successfully detects key fraud features within the Ponzi scheme dataset, reducing the number of features from 70 to only 10 while maintaining a high level of accuracy. The main strength of this proposed method lies in its ability to detect clever Ponzi schemes from their inception, offering valuable insights to combat these financial threats effectively.
Mainstream blockchain games have drawn criticism for prioritizing economic systems over gameplay experience. Influenced by these economically-centered games, existing research on blockchain games predominantly focuses on the financial sector. We have developed BranchClash, a fully on-chain tower defense game on the Sepolia testnet of Ethereum. It introduces chain collaboration, a novel non-economically-centered game mechanism inspired by blockchain technology. BranchClash aims to expand unique game mechanics in blockchain games and explore innovative cooperative modes within the decentralized ecosystem.
The current state of recycling systems is marked by significant impediments to their efficacy. A lack of transparency often pervades these systems, which may result in an increased likelihood of fraudulent and corrupt activity. Additionally, traceability pertaining to recycled materials frequently proves inadequate. Together, these inefficiencies in the collection and processing of recyclables can lead to higher costs and environmental impact. Furthermore, low incentives may deter individuals and businesses from participating in recycling initiatives. Certain recycling systems may also suffer from limited compatibility with specific materials, further reducing their effectiveness. To address these challenges, we propose a permissioned Ethereum blockchain-based system that aims to incentivise and encourage recycling practices in a transparent and secure manner. The platform’s modular and multi-layered design makes it adaptable to various recycling scenarios, allowing it to handle diverse types of recyclable materials. Automated and streamlined recycling processes are achieved through the use of smart contracts. The proposed system offers a secure, transparent, and efficient platform for the management of recycling processes, promoting environmentally responsible behaviour towards a circular economy. Potential applications for the system include waste disposal and recycling management for smart cities, waste management for organisations, and tracking and management of operations for recycling companies. The platform is highly versatile and can accommodate various use cases in the recycling industry, including those involving traceable and untraceable materials, as well as individual and corporate use cases.
Abstract: As Web3 and blockchain develop faster in many areas such as healthcare, social services, electronic voting and more. Crowdfunding applications are leveraging BSC's efficiency and low transaction costs to bridge the gap between blockchain and traditional finance through a hybrid model. It combines the user-friendly React-based interface, secure Solidity smart contracts, and Hardhat's development and testing capabilities to create a versatile and secure platform. The goal of this project is to identify the value gap in the current crowdfunding market and provide them with smart contracts with smart tools for application businesses created by Ethereum. This crowdfunding app represents a significant step forward in fundraising, meeting many needs of customers and poised to shape the future of crowdfunding with its new and innovative approach.
The phishing scams pose a serious threat to the ecosystem of Ethereum which is one of the largest blockchains in the world. Such a type of cyberattack recently has caused losses of millions of dollars. In this paper, we propose a Self-supervised IncrEmental deep Graph lEarning (SIEGE) model, for the phishing scam detection problem on Ethereum. To overcome the data scalability challenge, we propose splitting the original Ethereum transaction data and constructing transaction graphs for each split. Confronted with the minimal labeled data available, we resort to graph-based self-supervised learning. We design a spatial pretext task to learn high-quality node embeddings inside a single graph split, as well as an incremental learning paradigm and a temporal pretext task to facilitate information flow between different graph splits. To evaluate the effectiveness of SIEGE, we gather a real-world dataset consisting of six-month Ethereum transaction records. The results demonstrate that our model consistently outperforms baseline approaches in both transductive and inductive settings.
In this study, the five most well-known cryptocurrencies in the blockchain-based decentralized financing structure were compared with the centralized market interest rates, and it was examined whether there is a significant relationship between the changes in market interest rates and the prices of cryptocurrencies. Key findings indicate a significant relationship between most cryptocurrencies, such as Dash, Litecoin, Ethereum, and Bitcoin, with market interest rates. However, XRP emerges as an exception. In addition to the comparative analysis between cryptocurrencies and market interest rates, this study delves into the underlying mechanisms that govern these relationships. It explores the role of blockchain technology in shaping the decentralized financing structure and highlights the intricacies of various cryptographic algorithms. The research also emphasizes the need for specialized accounting practices that cater to the unique challenges posed by cryptocurrencies. This study bridges the understanding between conventional economic mechanisms and the innovative world of cryptocurrencies, offering inferences that are important for investors, financial analysts, and accountants in the digital age.
Blockchain technology has generated an influx of transaction data and complex interactions, posing significant challenges for traditional machine learning methods, which struggle to capture high-dimensional patterns in transaction networks. In this paper, we present the disentangled prototypical graph convolutional network (DP-GCN), an innovative approach to account classification in Ethereum transaction records. Our method employs a unique disentanglement mechanism that isolates relevant features, enhancing pattern recognition within the network. Additionally, we apply prototyping to disentangled representations, to classify scam nodes robustly, despite extreme class imbalances. We further employ a joint learning strategy, combining triplet loss and prototypical loss with a gamma coefficient, achieving an effective balance between the two. Experiments on real Ethereum data showcase the success of our approach, as the DP-GCN attained an F1 score improvement of 32.54%p over the previous best-performing GCN model and an area under the ROC curve (AUC) improvement of 4.28%p by incorporating our novel disentangled prototyping concept. Our research highlights the importance of advanced techniques in detecting malicious activities within large-scale real-world cryptocurrency transactions.
This article explores the relationship between green energy and cryptocurrencies in the sustainable energy finance sector. The research findings contribute to our understanding of the application of green economy practice, enabling investors in financial markets, policymakers, and stakeholders to make informed decisions and develop specific strategies. Adopting the green economy paradigm makes it possible to promote collaboration and innovation by integrating ethical and responsible principles that can improve the overall quality of processes and boost sustainable growth. Cryptocurrencies have been widely used as financial instruments over the last decade. Given the development of the cryptocurrency market and the growing awareness of greener and more energy-efficient tokens, the green economy has become a popular topic for understanding economic and political issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green energies. Therefore, this study examines the long- and short-term relationships between dirty cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), clean cryptocurrencies such as Cardano (ADA), Ripple (XRP), Stellar (XLM), and green energies such as ISE Clean Edge Global Wind Energy, S&amp;amp;P Global Clean Energy, S&amp;amp;P TSX Renewable Energy and Clean Technology, Solactive China Clean Energy, in the period from January 2020 to September 2023. The results show that diversification is key, with clean cryptocurrencies such as ADA, XLM and XRP offering diversification opportunities alongside &quot;dirty&quot; cryptocurrencies such as BTC and ETH. Although sustainable energy indices show mixed evidence in the long and short term, they remain relevant for those who focus on clean energy investments. It is also becoming increasingly relevant for investors in sustainable portfolios to assess their environmental impact, especially for energy-intensive cryptocurrencies, and it is advisable to explore sustainable blockchain technologies.
Digital currencies have become an increasingly popular topic of discussion in recent years. Digital currencies are virtual forms of currency that operate outside the traditional banking system. They are based on cryptographic technologies and are often decentralized, meaning they are not controlled by a central authority. The most well-known digital currency is Bitcoin, but there are many other types of digital currencies in existence. Digital currencies can be used to purchase goods and services online or transferred between users directly without intermediaries like banks. They have gained popularity due to their potential for increased security, transparency, and efficiency in financial transactions. In today's digital currency, a variety of digital currencies emerge in an endless stream, and crypto technology is also constantly developing to improve the security of digital currency payments. In section 2, this paper briefly introduces several common digital currencies and encryption algorithms, and in section 3, this paper introduces these typical digital currencies in detail through the analysis of representative literature. Bitcoin is mainly encrypted based on blockchain technology, and its encryption principle is mainly divided into three parts: public key encryption, hash function, and proof of work. Ethereum is a distributed blockchain platform with encryption principles similar to Bitcoin, including public key encryption and hashing algorithms. Ripple is a distributed cryptocurrency. Its encryption principle mainly adopts the public-private key encryption system. In terms of encryption technology, blockchain technology, the Hash algorithm and symmetric and asymmetric encryption are also popular encryption algorithms in digital currencies.
Andrei C. Azevedo, Eder J. Scheid, Muriel Figueredo Franco, Lisandro Zambenedetti Granville
Besides the main blockchain use-case of exchanging cryptocurrencies, Distributed Applications (DApps) can also be developed on top of such a technology. However, due to the size of popular blockchains and price, testing these DApps in a real-world environment becomes challenging. Thus, blockchain emulators were proposed to address such as issue. This paper presents the experience of emulating an Ethereum network using a Docker-based lightweight testbed developed for Software Defined Networks (SDN).
Victor Takashi Hayashi, Renato Penha, Gabriela Silva, Lucas Pacheco Vieira · 8 authors
Uma solução foi proposta para criar pools de seguros mútuos eficientes, baratos e seguros na blockchain Ethereum para uma startup de seguros localizada em São Paulo (SP), Brasil. Os grupos são formados por pessoas que se unem para proteger contra riscos predeterminados e são autoadministrados até certo ponto. Os resultados mostram que a administração do grupo é realizada por meio de contratos inteligentes que executam automaticamente as condições acordadas pelas partes. Todas as regras de negócios e reservas financeiras são mantidas no contrato inteligente. Os usuários interagem com o sistema em uma aplicação web que utiliza uma API Web3, que possui uma área de cliente e uma área de seguros P2P para gestão de novos grupos e atuação no processo de indenização.
José Antonio Núñez Mora, Mario Iván Contreras-Valdez, Roberto J. Santillán‐Salgado
This paper reports our findings on the return dynamics of Bitcoin and Ethereum using high-frequency data (minute-by-minute observations) from 2015 to 2022 for Bitcoin and from 2016 to 2022 for Ethereum. The main objective of modeling these two series was to obtain a dynamic estimation of risk premium with the intention of characterizing its behavior. To this end, we estimated the Generalized Autoregressive Conditional Heteroskedasticity in Mean with Normal-Inverse Gaussian distribution (GARCH-M-NIG) model for the residuals. We also estimated the other parameters of the model and discussed their evolution over time, including the skewness and kurtosis of the Normal-Inverse Gaussian distribution. Similarly, we determined the parameters that define the evolution of the estimated variance, i.e., the parameters related to the fitted past variance, square error and long-term average value. We found that, despite the market uncertainty during the COVID-19 emergency period (2020 and 2021), the selected cryptocurrencies’ return volatility and kurtosis were even greater for several other subperiods within our sample’s time frame. Our model represents an analytical tool that estimates the risk premium that should be delivered by Bitcoin and Ethereum and is therefore of interest to risk managers, traders and investors.