Abstrak - Tingginya volatilitas Bitcoin mendorong kebutuhan model prediktif presisi untuk landasan keputusan investasi optimal. Studi ini mengimplementasikan algoritma Random Forest guna memprediksi pergerakan harga berdasarkan 1.766 data historis harian (Januari 2020-Oktober 2024). Pra-pemodelan diawali analisis korelasi Pearson dengan ambang batas 0.5, yang menyeleksi fitur High (0,999), Open (0,998), dan Low (0,997) sebagai prediktor akibat asosiasi kuat, sementara Volume dan Change% dieliminasi karena kontribusi minimal. Pengujian membandingkan dua strategi pembagian data: partisi acak dan tidak acak (rasio 80:20), menggunakan metrik Mean Absolute Percentage Error (MAPE) dan Akurasi. Hasil empiris menunjukkan partisi acak unggul (MAPE 1,34%; Akurasi 98,66%) dibanding partisi tidak acak (MAPE 1,7%; Akurasi 98,3%). Konklusi menegaskan efektivitas signifikan algoritma Random Forest, dengan keberhasilan bergantung pada ketepatan seleksi fitur dan adaptasi strategi pembagian data terhadap karakteristik dataset.Kata kunci: Bitcoin; Random Forest; Prediksi Harga; Korelasi Pearson; MAPE; Abstract - The high volatility of Bitcoin necessitates precise predictive models for optimal investment decision-making. This study implements the Random Forest algorithm to predict price movements based on 1,766 daily historical data points (January 2020 - October 2024). Pre-modeling began with Pearson correlation analysis with a threshold 0.5, which selected the High (0.999), Open (0.998), and Low (0.997) features as predictors due to their strong association, while Volume and Change% were eliminated due to their minimal contribution. The testing compared two data splitting strategies: random and non-random (80:20 ratio), using the Mean Absolute Percentage Error (MAPE) and Accuracy metrics. Empirical results showed that random partitioning outperformed non-random partitioning (MAPE 1.34%; Accuracy 98.66% compared to MAPE 1.7%; Accuracy 98.3%). The conclusion confirms the significant effectiveness of the Random Forest algorithm, with success depending on the accuracy of feature selection and adapting the data splitting strategy to the characteristics of the dataset. Keywords: Bitcoin; Random Forest; Price Prediction; Pearson Correlation; MAPE;
Smart contracts, a revolutionary technology that offers a digital alternative to conventional contracts, are popular. Smart contracts also known as automated digital contracts are becoming common in various countries due to their efficiency and openness. Various national and global forums have agreed that smart contracts might alter contract enforcement and boost economic development in India. Given this, it’s crucial to understand the Indian Contract Act, (ICA) 1872 stance on smart contracts. ICA requires testing smart contracts for contractual validity before entering the uncharted seas of autonomous and anonymous digital contracting. This experiment raises many issues, especially given the law’s strict procedural structure. This article refutes the claim that smart contracts should be regulated by self-regulation. Rather author prefers a broad interpretation of substantive contractual law to harmonize smart contracts under the ICA, following common law’s flexibility. It is shown that smart contracts are built on the same principles as common law contracts and deepen our research in the framework of Indian law and precedent. Similar approaches from other countries support this perspective. Although many legislations require change, it is believed that a smart contract law is not needed. The paper concludes by proposing solutions to the potential obstacles that may arise due to present approach.
Rooftop solar (RTS) represents a critical component of India’s clean energy transition, offering decentralized generation, reduced transmission losses, and potential resilience benefits. Yet, despite ambitious national targets and substantial technical potential, RTS adoption has lagged behind expectations. This narrative review synthesizes peer-reviewed literature (2019–2025), government program documents, and policy reports to examine the trends, barriers, enablers, economics, regional signals, stakeholder outcomes, and policy implications shaping rooftop solar adoption in India. Findings indicate that commercial and industrial consumers have historically dominated the sector due to favorable tariffs and access to credit, while residential uptake accelerated only after the launch of flagship initiatives such as PM Surya Ghar. Persistent barriers include high upfront costs, affordability gaps, regulatory uncertainty, procedural delays, information asymmetries, and built environment constraints. At the same time, innovations such as simplified subsidy pipelines, digitalized approval portals, DISCOM performance incentives, vendor certification, and emerging business models including RESCO/OPEX and group or virtual net metering demonstrate viable pathways to expand adoption. The review identifies future research needs in program evaluation, financial innovation, grid integration, apartment governance, and quality assurance, and emphasizes the importance of stable regulatory frameworks, inclusive finance, and community-oriented models.
The unprecedented growth of digital art in the contemporary creative economy has empowered artists to reach global audiences, yet it has simultaneously amplified threats of copyright infringement, piracy, and unauthorized duplication. Traditional intellectual property frameworks, while legally robust, are often ill-suited to address the speed, borderless nature, and technological complexity of digital content circulation. Blockchain technology emerges as a transformative paradigm, introducing decentralized and tamper-proof mechanisms for digital rights management. Through non-fungible tokens (NFTs), smart contracts, and immutable ledgers, blockchain provides verifiable proof of authorship, facilitates transparent provenance tracking, and automates royalty distribution without reliance on intermediaries. This manuscript critically examines the role of blockchain in strengthening copyright protection for digital artists by combining an extensive review of existing literature with statistical survey data drawn from practicing artists across multiple regions. Findings reveal that while blockchain adoption is gaining momentum, barriers such as regulatory uncertainty, high transaction costs, energy inefficiency, and limited user literacy constrain large-scale implementation. The study demonstrates that blockchain can enhance creative autonomy, ensure fair economic participation, and foster trust in digital art ecosystems, but its success depends on legal integration, sustainable infrastructure, and artist-centered governance. This research contributes to the discourse by offering a multi-layered framework for blockchain-enabled copyright systems, bridging technological innovation with socio-legal realities, and outlining directions for future policy and research in intellectual property protection.
Xihan Xiong, Zhipeng Wang, Qin Wang, William Knottenbelt
Decentralized communication is becoming an important use case within Web3. On Ethereum, users can repurpose the transaction input data field to embed natural-language messages, commonly known as Input Data Messages (IDMs). However, as IDMs gain wider adoption, there has been a growing volume of toxic content on-chain. This trend is concerning, as Ethereum provides no protocol-level support for content moderation. We propose two moderation frameworks for Ethereum IDMs: (i) BUILDERMOD, where builders perform semantic checks during block construction; and (ii) USERMOD, where users proactively obtain moderation proofs from external classifiers and embed them in transactions. Our evaluation reveals that BUILDERMOD incurs high block-time overhead, which limits its practicality. In contrast, USERMOD enables lower-latency validation and scales more effectively, making it a more practical approach in moderation-aware Ethereum environments. Our study lays the groundwork for protocol-level content governance in decentralized systems, and we hope it contributes to the development of a decentralized communication environment that is safe, trustworthy, and socially responsible.
Dini Rohmayani, Ilham Alfath, Castaka Agus Sugianto
Abstrak - Implementasi Non-Fungible Token (NFT) sering menghadapi masalah permanensi data karena ketergantungan pada penyimpanan terpusat yang rentan terhadap penghapusan dan perubahan. Penelitian ini mengembangkan aplikasi web berbasis Decentralized Application (DApp) untuk pembuatan Non-Fungible Token (NFT) yang mengintegrasikan InterPlanetary File System (IPFS) dengan Smart Contract ERC-721 pada blockchain Ethereum. Metode pengembangan menggunakan pendekatan waterfall dengan implementasi React.js dan Next.js untuk frontend serta Solidity untuk smart contract. Sistem dirancang dengan arsitektur three-tier yang memfasilitasi pembuatan koleksi Non-Fungible Token (NFT) melalui kontrak Factory dan pengelolaan token melalui NFTCollection, dengan metadata dan aset digital disimpan menggunakan Content Identifier (CID) pada InterPlanetary File System (IPFS). Pengujian blackbox menunjukkan seluruh fungsi sistem berjalan sesuai spesifikasi, sementara User Acceptance Testing (UAT) dengan 24 responden menghasilkan tingkat penerimaan 90%. Hasil penelitian membuktikan bahwa integrasi InterPlanetary File System (IPFS) dengan smart contract ERC-721 dapat mengatasi permasalahan permanensi metadata dan aset digital, sekaligus menyederhanakan proses minting Non-Fungible Token (NFT) bagi pengguna non-teknis melalui antarmuka yang intuitif.Kata kunci: Non-Fungible Token (NFT); ERC-721; IPFS; Kontrak Pintar; Blockchain; Abstract - Podo Practical implementations of Non-Fungible Tokens (NFTs) often face data permanence issues due to reliance on centralized storage systems vulnerable to deletion and modification. This research develops a web-based Decentralized Application (DApp) for NFT creation that integrates the InterPlanetary File System (IPFS) with ERC-721 Smart Contracts on the Ethereum blockchain. The development methodology employs a waterfall approach with React.js and Next.js for frontend implementation and Solidity for smart contracts. The system is designed with a three-tier architecture facilitating NFT collection creation through the NFTFactory contract and token management through NFTCollection, with metadata and digital assets stored using Content Identifiers (CID) on IPFS. Black box testing demonstrates that all system functions operate according to specifications, while User Acceptance Testing (UAT) with 24 respondents yields an acceptance rate of 90%. The research findings prove that integrating IPFS with ERC-721 smart contracts addresses metadata and digital asset permanence issues while simplifying the NFT minting process for non-technical users through an intuitive interface.Keywords: Non-Fungible Token (NFT); ERC-721; IPFS; Smart Contract; Blockchain;
The rapid expansion of digital assets has created a conflict between technological innovation and environmental, social, and governance (ESG) principles, particularly concerning the energy consumption of legacy consensus mechanisms. This has led to the emergence of "sustainable" cryptocurrencies, raising the critical question of whether the market financially rewards sustainability. This study quantitatively investigates the existence and magnitude of an "ESG premium" in the digital asset market. A quasi-longitudinal study was conducted on a panel dataset of 20 cryptocurrencies (10 sustainable, 10 traditional) from January 1, 2021, to December 31, 2024. A detailed, transparent composite ESG score was developed to measure sustainability. The primary analysis utilized a panel data fixed-effects regression model to assess the relationship between asset prices and ESG scores, controlling for market capitalization, trading volume, market-wide indices, and key technological factors like protocol age, scalability, and developer activity. To address endogeneity and validate causality, we employed models with lagged independent variables. Further robustness checks were performed across bull and bear market sub-periods. A GARCH (1,1) model was used to analyze differences in price volatility. The primary regression model reveals a statistically and economically significant positive relationship between ESG scores and cryptocurrency prices. A 10-point increase in the ESG score is associated with a 4.1% price premium (b=0.0041, p < 0.001), even after controlling for technological modernity. This finding remains robust in models using lagged variables and across different market cycles. GARCH analysis confirms that sustainable cryptocurrencies exhibit significantly lower price volatility. In conclusion, the findings provide strong, robust empirical evidence for a persistent ESG premium in the cryptocurrency market. This suggests that investors price in the perceived long-term viability, reduced risk profile, and ethical alignment of sustainable assets, signaling a maturation of the market where non-financial, sustainability-focused metrics are integral to asset valuation.
Cryptocurrency money-laundering forensic analysis after Web3 incidents faces challenges such as fragmented evidence, expanding transaction paths, and cross-chain discontinuity. Existing Web3 AML methods largely rely on manual clues and heuristic or graph-search-based tracing, with outputs limited to lists of suspicious addresses and lacking path-level evidence and verifiable explanations. Directly applying general-purpose large language models to raw transaction flows also struggles to ensure evidence constraints and result verifiability. To address these limitations, this paper presents RISKTAGGER, an LLM-guided agent for forensic tracing of Web3 cryptocurrency money laundering. RISKTAGGER embeds the LLM as an evidence-constrained decision component within a controlled tracing loop. It extracts case clues from public incident materials, recursively expands a risk-labeled fund-flow graph over on-chain evidence, and generates evidence-organized reports for analyst review. We evaluate it on five real-world incidents spanning multiple years and covering heterogeneous attack patterns and laundering path structures. We further conduct cross-case generalization analysis, baseline comparison, component ablation, and LLM backend analysis. In the main Bybit case, the system achieves a 97.33% address recall and a 98.69% expert-reviewed sampled address precision. Across the other four incidents, it achieves 95.24-100.00% address recall and 91.27-100.00% expert-reviewed address precision. The cross-case results further show that the complexity of Web3 money laundering arises from heterogeneous mechanisms, including short-cycle fund fragmentation, long-range laundering paths, interwoven DeFi services, and deterministic denomination splitting. RISKTAGGER can recover case-related fund paths, identify high-priority risk accounts, and organize public evidence into verifiable forensic reports.
Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could address disruptions stemming from supplier instability, poor traceability, and regulatory and environmental pressures, while highlighting its potential to drive ethical sourcing and environmentally responsible practices. The structured discussions were guided by theoretical frameworks and expert evaluations were synthesized into two analytical matrices illustrating DLT’s influence on SCR. The findings reveal that the contribution of DLT to SCR and sustainability is highly context-dependent, with its effectiveness hinging on how it is embedded within governance structures and aligned with the interplay of complementary technologies. Building on these insights, the study presents the DLT-LFL (Distributed Ledger Technology–Learning Feedback Loop) framework, which integrates sensing, decision-making, adaptation, and predictive learning from distributed operational data, allowing supply chains to better anticipate disruptions, adjust processes dynamically, and continuously strengthen resilience and sustainable practices. The study also develops a practical checklist to assess how effective DLT applications and their integration with predictive and AI-driven analytics reduce vulnerabilities, strengthen capabilities, mitigate risks, and support adaptive decision-making.
Smart contract adalah program yang dapat memastikan bahwa aturan atau perjanjian di jaringan basis data terdistribusi berlaku untuk transaksi yang terjadi. Penelitian ini adalah penelitian hukum yuridis normatif dengan sifat penelitian deskriptif. Teknik pengumpulan data dilakukan melalui studi kepustakaan. Analisis dalam penelitian ini dilakukan secara kualitiatif. Berdasarkan hasil penelitian ditemukan bahwa pengaturan mengenai smart contract di Indonesia belum diatur secara jelas dalam suatu regulasi. Smart contract dapat diterapkan di Indonesia asalkan sesuai dengan hukum dan tidak melanggar norma-norma sosial. Keabsahan hukum atas kehadiran smart contract dikaitkan dengan transaksi elektronik memerlukan kerangka hukum yang jelas dan dukungan dari berbagai pihak, sebab regulasi mengenai smart contract di Indonesia masih belum sepenuhnya terdefinisi. Sehingga kepastian hukum terhadap keabsahan hukum atas kehadiran smart contract belum dapat diwujudnya sepenuhnya, dikarenakan sandungan dalam regulasi yang belum jelas. Implementasi smart contract pada teknologi blockchain dalam kaitannya dengan praktik Notaris sebagai pejabat umum tidak dapat sepenuhnya menghapuskan peran Notaris selaku pejabat umum yang diberikan wewenang oleh ketentuan UUJN.
Electronic voting (e-voting) has become an essential topic in the modernization of democratic systems, with promises of accessibility, faster counting, and reduced logistical challenges compared to traditional paper ballots. Yet, widespread adoption has been hindered by persistent trust and security concerns. Vulnerabilities such as malware, server compromise, insider threats, and limited verifiability have generated skepticism regarding the integrity of e-voting platforms. Blockchain technology has emerged as a disruptive innovation capable of reshaping this discourse. Its intrinsic properties—immutability, decentralization, transparency, and consensus-driven validation—directly address many of the fundamental challenges associated with securing digital elections. This manuscript provides a comprehensive exploration of blockchain-based electronic voting, with particular emphasis on the trust and security challenges that shape its practical deployment. Drawing on global case studies, theoretical models, and simulation insights, the research examines how blockchain can ensure tamper resistance, facilitate end-to-end verifiability, and empower voters through transparent audit trails. Key challenges such as scalability bottlenecks, voter anonymity risks, usability barriers, and regulatory gaps are analyzed in depth. The results indicate that hybrid blockchain architectures, which integrate advanced cryptographic techniques such as zero-knowledge proofs, homomorphic encryption, and sharding, hold promise for balancing the competing demands of scalability, privacy, and trust. Furthermore, blockchain must be supported by strong institutional frameworks, inclusive accessibility measures, and continuous technical audits to achieve legitimacy in electoral processes. By systematically mapping both the opportunities and limitations, this research contributes to the ongoing discourse on how technology can strengthen democratic resilience in the digital era. Ultimately, blockchain-enabled voting should be regarded not as a replacement but as an augmentation of existing systems, combining the strengths of distributed technologies with constitutional safeguards to advance secure, transparent, and inclusive electoral participation.
Mazin Abed Mohammed, Mohd Khanapi Abd Ghani, Israa Badr Al-Mashhadani, Sajida Memon · 7 authors
The exponential growth of healthcare Internet of Things (IoT) data necessitates secure, low-latency analytics that extend beyond centralized architectures. This paper presents BDAFL DNN, a blockchain-integrated data analytics framework that combines Federated Learning (FL) and Deep Neural Networks (DNNs) for real-time, privacy-preserving healthcare analytics across edge and cloud resources. Local devices such as smartwatches and phones collect noninvasive time series sensor streams (heart rate, temperature, and abdomen sensors), perform on device DNN training, and send only model updates to healthcare edge nodes, where a blockchain ledger validates updates for integrity and traceability; validated updates are then aggregated in the cloud via FL to produce a global model without sharing raw data. In a simulation study against representative baselines, BDAFL DNN reduced execution time, energy use, and resource consumption, lowered the deadline miss ratio, and improved blockchain validation correctness. These results show that integrating blockchain with FL-driven edge and cloud DNN analytics can deliver scalable, secure, and timely insights for future healthcare IoT systems. Reason for Expression of Concern:The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Blockchain-Powered Dynamic Segmentation in Personal Health Record”. The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility. This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.See expression of concern available at:https://doi.org/10.58496/2026/017 https://mesopotamian.press/journals/index.php/CyberSecurity/article/view/1041
Lingling Xia, Tao Zhu, Zhengjun Jing, Qun Wang · 7 authors
Digital currencies, led by Bitcoin and USDT, are characterized by decentralization and anonymity, which obscure the identities of traders and create a conducive environment for illicit activities such as drug trafficking, money laundering, cyber fraud, and terrorism financing. Focusing on the USDT-TRC20 token on the Tron blockchain, we propose a two-layer transaction network-based approach for virtual currency address identity recognition for digging out hidden relationships and encrypted assets. Specifically, a two-layer transaction network is constructed: Layer A describes the flow of USDT-TRC20 between on-chain addresses over time, while Layer B represents the flow of TRX between on-chain addresses over time. Subsequently, an identity metric is proposed to determine whether a pair of addresses belongs to the same user or group. Furthermore, transaction records are systematically acquired through blockchain explorers, and the efficacy of the proposed recognition method is empirically validated using dataset from the Key Laboratory of Digital Forensics. Finally, the transaction topology is visualized using Neo4j, providing a comprehensive and intuitive representation of the traced transaction pathways.
The integration of Internet of Things (IoT) technologies into public healthcare enables continuous monitoring and sustainable health management. However, conventional frameworks often depend on transmitting and storing raw personal data on centralized servers, posing challenges related to privacy, security, ethical compliance, and long-term sustainability. This study proposes a privacy-preserving framework that avoids the exposure of true health-related data. Sensor nodes encrypt collected measurements and collaborate with a secure computation core to evaluate health indicators under homomorphic encryption, maintaining confidentiality. For example, the system can determine whether a patient’s heart rate within a monitoring window falls inside clinically recommended thresholds, while the framework remains general enough to support a wide range of encrypted computations. A compliance verification client generates zero-knowledge range proofs, allowing external parties to verify whether health indicators meet predefined conditions without accessing actual values. Simulation results confirm the correctness of encrypted computation, controllability of threshold-based compliance judgments, and resistance to inference attacks. The proposed framework provides a practical solution for secure, auditable, and sustainable real-time health assessment in IoT-enabled public healthcare systems.
This study investigates the dynamic relationship between order flow toxicity, measured by the volume-synchronized probability of informed trading (VPIN), and price jumps in the Bitcoin market using high-frequency data and vector autoregressive model (VAR) modelling. By integrating behavioral finance theory to market microstructure framework, we explore how informed trading activity influences jumps in price, and how traders respond to such volatility. Our findings reveal that VPIN significantly predicts future price jumps, with positive serial correlation observed in both VPIN and jump size, suggesting persistent asymmetric information and momentum effects. On the contrary, price jumps occasionally affect VPIN. This study also identifies time-zone and day-of-the-week effects in VPIN, highlighting the role of global trading patterns. The results are robust among the choices of jump tests including Jiang and Oomen (2008) test which is empirically robust against market microstructure noise. These results contribute to a deeper understanding of intraday volatility in cryptocurrency markets and offer practical implications for risk management, trading strategy design, and regulatory oversight.
In today’s digital economy, traditional forms of ownership are undergoing significant changes due to the rise of new technologies, including the spread of Non-Fungible Tokens (NFTs). "Non-fungible" in this context means that each token is unique and cannot be easily exchanged for a similar item, as is the case with conventional digital or physical currencies. A token itself is a digital unit that can represent a digital asset, a piece of art or a unique item, or the granting of a service and so on. This study aims to analyze the role of NFTs as a tool that transforms ownership within the digital space and fosters new economic relationships. The research is grounded in the fundamentals of blockchain technology and integrates economic theories, specifically value theory and contemporary models of capital, in the context of NFTs. The article employs an interdisciplinary approach and examines the mechanisms of uniqueness and decentralized ownership inherent to NFTs, which are reshaping the structure and efficiency of the intangible assets market. Special emphasis is placed on the impact of NFTs on the monetization of digital assets, value formation, and the dynamics of the creative industry. Particular attention is also given to the speculative nature of the market, regulatory challenges, and the prospects for economic sustainability. The findings confirm that NFTs represent not only an economic innovation that transforms ownership mechanisms, but also pose complex challenges related to the legal protection of assets and market stability. The conclusions indicate that NFTs are not merely tools for transforming digital ownership but also play a significant role in shaping new models of the digital economy—models that require further research and regulatory attention. Keywords: NFT, digital economy, ownership transformation, intangible assets, blockchain, economic innovation, monetization, legal regulation.
In today’s financial landscape, customer onboarding and lending workflows are increasingly scrutinized for inefficiencies, security vulnerabilities, and compliance risks. Traditional processes rely heavily on centralized databases, manual verifications, and redundant Know Your Customer (KYC) checks, all of which contribute to high operational costs, delays, and susceptibility to fraud. As financial institutions seek more resilient and transparent systems, the integration of blockchain and distributed ledger technologies (DLT) emerges as a promising solution. This paper explores how blockchain—particularly permissioned or consortium-based architectures—can transform onboarding and lending processes by introducing secure, tamper-proof, and auditable transaction records. We present a conceptual framework that leverages smart contracts, decentralized identity (DID), and verifiable credentials (VC) to automate and streamline key steps in customer verification, loan approval, and regulatory reporting. By enabling shared, real-time access to validated information among trusted parties, DLT can reduce duplication, enhance trust, and improve compliance with regulatory mandates such as AML/KYC and data protection laws. The study also evaluates practical considerations, including system interoperability, privacy challenges, governance models, and legal implications. Case examples and pilot initiatives are reviewed to ground the theoretical model in real-world implementations. Ultimately, this paper aims to provide a comprehensive foundation for understanding and applying blockchain-based systems in the financial sector’s most sensitive workflows.
Abstract—The paradigm of digital identity is rapidly shifting from centralized monopolistic control toward decentralized user- centric frameworks to meet the demands of Web3, immer- sive computing and trustless interactions. Traditional identity systems expose users to privacy breaches, vendor lock-in and cross-platform incompatibilities, creating barriers for seamless adoption. To overcome these challenges DIGICRED introduces a decentralized identity and credential system built on Self- Sovereign Identity (SSI) principles leveraging Decentralized Iden- tifiers (DIDs) and blockchain-based cryptographic proofs as the foundation for trust. A verifiable credential layer enables selective disclosure of tamper-proof claims ranging from aca- demic certifications to government-issued IDs preserving privacy while ensuring interoperability. Complementing this a multi- dimensional reputation system fosters trust in anonymous en- vironments, mitigates Sybil attacks and incentivizes meaningful participation across decentralized applications. By integrating privacy-preserving technologies, compliance-aware architectures and scalable trust mechanisms DIGICRED redefines identity management for Web3. This shift marks the emergence of secure portable and user-controlled digital identities laying the groundwork for the future of decentralized applications and cross-platform digital ecosystems. Index Terms—Self-Sovereign Identity (SSI), Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), Blockchain, Web3, Digital Identity, Privacy Preservation, Reputation Systems, Trust Management, Cross-Platform Interoperability. .
Arya Ganendra, Neva Dian Permana, Muhammad Faiz, H. B. J. Clifford
Decentralized Finance (DeFi) proposes a paradigm shift towards a democratized financial ecosystem governed by its users. This vision of decentralization is predicated on the distribution of governance tokens. However, the verity of this claim lacks rigorous empirical validation, raising concerns about a potential "decentralization illusion." This study quantitatively investigates the concentration of governance power within leading DeFi protocols to empirically test this narrative. We employed a multi-faceted quantitative triangulation framework using on-chain data from three archetypal DeFi protocols, selected to represent the core sectors of the ecosystem: a lending market (ProtoLend), a decentralized exchange (ProtoSwap), and a yield aggregator (ProtoYield). Our methodology integrates: (1) Empirical Network Analysis based on on-chain voting power delegation to map the topology of influence; (2) Economic Inequality Metrics, including the Gini Coefficient and Lorenz Curve Analysis, to quantify the distribution of governance tokens; and (3) Systemic Risk Assessment via the Nakamoto Coefficient to determine the minimum number of colluding actors required for a 51% governance attack. The empirical network analysis revealed a distinct core-periphery topology across all protocols, indicative of highly centralized influence structures. This was substantiated by extreme economic inequality, with Gini coefficients of 0.91 for ProtoLend, 0.95 for ProtoSwap, and 0.89 for ProtoYield. Lorenz curves visually confirmed that a minuscule fraction of holders controls the vast majority of voting power. The Nakamoto coefficients were critically low, calculated at 8 for ProtoLend, 5 for ProtoSwap, and 11 for ProtoYield, exposing profound vulnerabilities to collusion and capture. In conclusion, our findings provide robust, triangulated evidence of a pervasive "decentralization illusion" within DeFi. Governance power is not distributed but is instead highly concentrated, replicating the plutocratic power dynamics of traditional finance. This concentration poses significant systemic risks and fundamentally challenges the core value proposition of the DeFi ecosystem.
The rise of centralised social networks has consolidated power among a few major technology companies, raising critical concerns about privacy, censorship, and transparency. In response, decentralised alternatives, including Web3 platforms like Decentralised Social (DeSo) and Fediverse platforms such as Mastodon, have gained increasing attention. While prior research has explored individual aspects of decentralised networks, comparisons between Fediverse and Web3 platforms remain limited, and the unique dynamics of Web3 networks like DeSo are not well understood. This study provides the first in-depth study of DeSo, characterising user behaviour, discourse, and economic activities, and compares these with Mastodon and memo.cash . We collected over 3.1M posts from 13K users on DeSo and Mastodon, along with 11M DeSo on-chain transactions via public APIs. Our analysis reveals that while DeSo and Mastodon share similarities in passive content engagement, they differ in their use of URLs, hashtags, and community focus. DeSo is primarily oriented around Decentralised Finance (DeFi) topics, whereas Mastodon hosts diverse discussions with an emphasis on news and politics. Despite DeSo’s decentralised social graph, its transaction graph remains centralised, underscoring the need for further decentralisation in Web3 platforms. Additionally, while wealth inequality exists on DeSo, low transaction fees promote user participation irrespective of financial status. These findings provide new insights into the evolving landscape of decentralised social networks and highlight critical areas for future research and platform development.
We argue that the principal application for blockchain technology will not be in the financial sector, but rather in maintaining decentralized human governance, from archives to transparent policies encoded in the blockchain in the form of smart contracts.. Such decentralized, blockchain-grounded governance comes not a moment too soon, as nation states are dissolving before our eyes. Will blockchain-based communities replace the nation state? What are the prospects and dangers of this development?
Raffaele Cristodaro, Benjamin Kraner, Claudio J. Tessone
This paper investigates the impact of sanctions on Tornado Cash, a smart contract protocol designed to enhance transaction privacy. Following the U.S. Department of the Treasury's sanctions against Tornado Cash in August 2022, platform activity declined sharply. We document a significant and sustained reduction in transaction volume, user diversity, and overall protocol utilization after the sanctions were imposed. Our analysis draws on transaction data from three major blockchains: Ethereum, BNB Smart Chain, and Polygon. We further examine developments following the partial lifting and eventual removal of sanctions by the U.S. Office of Foreign Assets Control (OFAC) in March 2025. Although activity partially recovered, the rebound remained limited. The Tornado Cash case illustrates how regulatory interventions can affect decentralized protocols, while also highlighting the challenges of fully enforcing such measures in decentralized environments.
Raffaele Cristodaro, Benjamin Kraner, Claudio J. Tessone
Tornado Cash is a decentralised mixer that uses cryptographic techniques to sever the on-chain trail between depositors and withdrawers. In practice, however, its anonymity can be undermined by user behaviour and operational quirks. We conduct the first cross-chain empirical study of Tornado Cash activity on Ethereum, BNB Smart Chain, and Polygon, introducing three clustering heuristics-(i) address-reuse, (ii) transactional-linkage, and (iii) a novel first-in-first-out (FIFO) temporal-matching rule. Together, these heuristics reconnect deposits to withdrawals and deanonymise a substantial share of recipients. Our analysis shows that 5.1 - 12.6% of withdrawals can already be traced to their originating deposits through address reuse and transactional linkage heuristics. Adding our novel First-In-First-Out (FIFO) temporal-matching heuristic lifts the linkage rate by a further 15 - 22 percentage points. Statistical tests confirm that these FIFO matches are highly unlikely to occur by chance. Comparable leakage across Ethereum, BNB Smart Chain, and Polygon indicates chain-agnostic user misbehaviour, rather than chain-specific protocol flaws. These results expose how quickly cryptographic guarantees can unravel in everyday use, underscoring the need for both disciplined user behaviour and privacy-aware protocol design. In total, our heuristics link over $2.3 billion in Tornado Cash withdrawals to identifiable deposits, exposing significant cracks in practical anonymity.
Alison Gonçalves Schemitt, Henrique Fan da Silva, Roben Castagna Lunardi, Diego Kreutz · 6 authors
The advent of quantum computing poses a threat to the security of traditional encryption algorithms. This has motivated the development of post-quantum cryptography (PQC). In 2024, the National Institute of Standards and Technology (NIST) standardized several PQC algorithms, marking an important milestone in the transition toward quantum-resistant security. Blockchain systems fundamentally rely on cryptographic primitives to guarantee data integrity and transaction authenticity. However, widely used algorithms such as ECDSA, employed in Bitcoin, Ethereum, and other networks, are vulnerable to quantum attacks. Although adopting PQC is essential for long-term security, its computational overhead in blockchain environments remains largely unexplored. In this work, we propose a methodology for benchmarking both PQC and traditional cryptographic algorithms in blockchain contexts. We measure signature generation and verification times across diverse computational environments and simulate their impact at scale. Our evaluation focuses on PQC digital signature schemes (ML-DSA, Dilithium, Falcon, Mayo, SLH-DSA, SPHINCS+, and Cross) across security levels 1 to 5, comparing them to ECDSA, the current standard in Bitcoin and Ethereum. Our results indicate that PQC algorithms introduce only minor performance overhead at security level 1, while in some scenarios they significantly outperform ECDSA at higher security levels. For instance, ML-DSA achieves a verification time of 0.14 ms on an ARM-based laptop at level 5, compared to 0.88 ms for ECDSA. We also provide an open-source implementation to ensure reproducibility and to encourage further research.