Blockchain Papers

Manegawindin Léonard Sawadogo, Didier Bassolé, Boureima Zerbo

No abstract is available for this record.

Kapil K. Jajulwar, Priya Dasarwar, Uma Yadav, Bhakti Prasad Thakre · 6 authors

Blockchain consensus mechanisms are important to ensure the safe validation of transactions. However, the limitations of high computational complexity, energy consumption, and mining latency restrict the scalability of blockchain in large-scale IP-based and wireless network environments. Current methods mainly rely on single optimization methods without jointly optimizing miner selection and hash computation, resulting in inferior performance under dynamic network conditions. To fill this gap, this study presents a new hybrid bioinspired optimization framework for efficient blockchain mining, integrating Genetic Algorithm (GA), Firefly optimization, and Particle Swarm Optimization (PSO) into a unified architecture to take advantage of their complementary strengths. The proposed method uses both historical and real-time performance metrics to determine the best mining nodes. The Firefly algorithm is used to optimize the selection of hash ranges to reduce CPU workload. PSO is used to select high-performance neighboring nodes for collaborative mining. The model is implemented using the NS-2 simulator and tested over a network of 1000 wireless nodes under different consensus protocols. The experimental results illustrate 4.3% decrease in computational complexity, 4% decrease in energy consumption, and 5% decrease in mining delay. The model further reduces mining complexity by up to 34.2% and reduces the energy utilization from 24.5% to 16.6%, demonstrating its effectiveness for scalable and energy-efficient blockchain deployment.

Himani Sharma, Tarun Maini, Krishna Kant Agrawal

No abstract is available for this record.

Lukas Stopfer, Thomas Purfürst, Hans-Ulrich Dietz

V-22 | Forsttechnik, Verfahrenstechnik II

Jaesung Kim, C.H. Cho, Jae Woo Lee

This study investigates whether the macroscopic statistical maturity of cryptocurrencies implies dynamical equivalence with traditional equity markets. We analyze high-frequency data (2020--2025) using the Complexity--Entropy Causality Plane (CECP) and directed horizontal visibility graphs (directed HVG) to uncover complex temporal patterns and time-directed structures in the return series. While conventional stylized facts show striking convergence across all assets, structural diagnostics reveal a compelling paradox: cryptocurrencies appear more locally random than the equity benchmark during ordinary periods, yet exhibit significantly stronger directional time-irreversibility around high-visibility return events. The absolute-return results show that large cryptocurrency fluctuations tend to begin abruptly and remain elevated afterward. Separate analyses of positive returns and negative-return magnitudes show that this pattern is shared across cryptocurrencies on the upside but varies across assets on the downside. We conclude that statistical maturity is only skin-deep; the underlying dynamical processes of mature cryptocurrencies remain fundamentally distinct from traditional benchmarks.

Yingzhu Chen

Decentralized Finance (DeFi) refers to an open financial ecosystem built on blockchain technology that does not require the participation of centralized institutions. The technology and operational mechanisms it employs represent a significant "paradigm mismatch" with the current financial regulatory framework. This paper examines the comprehensive impact of DeFi on existing financial regulation from multiple perspectives, including the blurring of regulatory authority and a lack of accountability; the difficulty in identifying regulatory targets and the ambiguity in determining their nature; the ineffectiveness of regulatory rules and the absence of relevant provisions; overlapping jurisdictions, and difficulties in enforcement. Through a comparative study of regulatory experiences in the United States, Europe, and other regions, this paper proposes solutions such as shifting the existing regulatory philosophy toward functional regulation, embedding compliance requirements into the underlying technology at the institutional level, and strengthening international cooperation at the operational level, while also discussing the specific context in China. This paper identifies a threefold paradigm mismatch between decentralized finance and traditional financial regulation, giving rise to multiple regulatory challenges such as difficulties in holding entities accountable, ambiguity in defining regulatory targets, ineffective regulatory rules, and obstacles to cross-border enforcement. A comparison of regulatory practices in the U.S. and Europe reveals that it is difficult for any single country to independently manage the risks associated with globalized DeFi.

Ira Nath, Sanjukta Chatterjee, Rangan Nath, Rumpa Paul · 5 authors

CryptC provides users with secure wallet services to protect their digital cryptocurrency assets as a modern cryptocurrency solution. Multiple platforms can adopt CryptC through the React Native interface while users can enjoy easy access using authentication from Firebase and Firestore for data and security features. Ganache with ethers.js enables the wallet to perform safe blockchain transactions while operating on a local Ethereum blockchain through its Ganache access. Secure compliance requirements are achieved by the platform through its transaction logging system and scalable functionality and biometric asset security measures, and balance update capabilities. The platform features an interface that combines professional and beginner user capabilities through an interactive dashboard, together with horizontal list presentation and user-focused design execution. The DeFi (Decentralized finance) ecosystem tool CryptC provides real-time operation capabilities that outperforms conventional wallet features like PIN base verification, Real-time Ethereum (ETH) transaction, minimalistic mobile-friendly UI etc. Our work provides comprehensive information about CryptC, along with its unique design specification through android App and security protocols, while validating the platform for payments at multiple operational levels.

Hui Cui, Haoze Cheng, James Boorman

Biometric authentication offers enhanced usability for digital payments, but traditional centralized architectures suffer from single points of failure. While blockchain integration promises decentralized trust, existing solutions often store biometric helper data (e.g., fuzzy commitments) directly on-chain. We demonstrate that such transparency, even in permissioned settings, exposes low-entropy biometric inputs to offline brute-force attacks and identity-linkage risks if the immutable ledger is accessed by malicious nodes. To resolve this transparency–privacy paradox, we propose a threshold-based decentralized authentication framework. Unlike prior works, our protocol keeps all sensitive Biometric-Enhanced Key Derivation (BEKD) tokens entirely off-chain, using the blockchain solely for freshness enforcement. We provide a game-based security analysis of brute-force resistance, unforgeability, and unlinkability. Our experimental results demonstrate that our scheme’s gas cost is acceptable, offering a robust solution for self-sovereign biometric identity.

Keisuke Suzuki

What is real has always been something we find , not something we make —or so philosophy has assumed. This paper argues otherwise. Characterizing reality through resistance rather than substance (the ways the world refuses a subject’s mastery), I distinguish three modalities correlative to epistemic, judgmental, and practical mastery: Substrate (matter’s resistance to representation), Contingency (the forceful givenness of experience that resists revision by judgment), and the Inexorable (structures’ resistance to intervention). Treating virtual environments, AI agents, and blockchain smart contracts not as proofs but as revelatory cases, I show that technology now extends the latter two modalities, Contingency and the Inexorable, artificially. The result is the paper’s central concept, Artificial Externality : human-made structures whose resistance to intervention is deliberately engineered to be practically insurmountable, even for their creators, and that thereby acquire an externality once attributed only to nature. Absoluteness, traditionally found, can now be produced. I close by drawing out the stakes for consciousness: our criteria for what counts as real quietly shape our criteria for what counts as conscious.

Muhammad Ali Hassan Ahmad, Muhammad Hashim Ali, Muhammad Ali Amer, Muhammad Naiman Jalil · 6 authors

A blockchain is a decentralized, secure ledger system that enables transparent and immutable record-keeping, essential for trust and security in digital transactions. Smart contracts are self-executing agreements encoded on a blockchain, enabling different parties to fulfill the terms of the agreement automatically. These contracts trigger corresponding actions when conditions are met, ensuring decentralized and transparent transactions. Writing reliable smart contracts is challenging due to the lack of standardization. To find security vulnerabilities, tools based on various approaches, including symbolic execution, are used. However, these tools often report a large number of false positives, raising concerns about their reliability. The time and effort spent investigating false positives diverts resources from addressing actual vulnerabilities. Therefore, such tools must also be evaluated according to the rate of false positives they exhibit. More importantly, the algorithms and heuristics used by the tools must be enhanced to distinguish between true vulnerabilities and false alarms. In this paper, we first demonstrate the prevalence of false positives in vulnerability reports generated by Mythril, a symbolic execution-based analysis tool for Ethereum smart contracts. We analyze the root causes of these inaccuracies and devise a rule-based approach based on the gained insight to reduce false positives. We implement our rules for the most impactful vulnerabilities in Mythril and assess the effectiveness of our approach. Our results show a significant reduction in false positives without compromising the detection of true vulnerabilities, thus enhancing the tool's reliability.

Jakub Kacper Szeląg, Aydin Abadi, Mohammad Naseri

Decentralization as a concept in computer science has existed for over half a century. Despite its fundamental role across domains such as security, distributed computing, artificial intelligence, cloud infrastructures, and Internet of Things (IoT) architectures, there remains no universally accepted definition of decentralization applicable across computer communication systems. This has become increasingly problematic with the emergence of decentralized AI and machine learning paradigms, including collaborative training, distributed inference, blockchain-based, and agentic AI, where decentralization is often treated as a core design objective. Meanwhile, existing approaches frequently conflate decentralization with related notions such as distribution of trust or specific implementation paradigms. Such ambiguity creates inconsistencies in system analysis, limits comparability between works, and weakens the rigor of formal reasoning surrounding communication architectures and protocol design. In this work, we define this research gap as the Decentralization Problem. We analyze the formal-semantic, epistemological, and pragmatic foundations of decentralization and introduce a graph-based ontology defining it as both relational and subject-specific property of computer communication systems. The framework formally distinguishes decentralization from distribution and supports evaluation through two novel metrics: Void Tolerance and Imperviousness. We also provide a browser-based implementation that enables automated classification and metric computation of arbitrary systems. Instantiations to federated learning and blockchain architectures show consistent, comparable assessments where existing definitions produce incomplete or contradictory conclusions, providing a domain-independent foundation for analysing decentralization across heterogeneous systems.

Kundan Mukhia, Sabat Rai, Vivek Shrivastav, Imran Ansari · 5 authors

Stablecoins have rapidly emerged as an important class of digital assets and a component of the digital financial ecosystem. Despite their growing importance, the statistical properties of stablecoin transaction activity remain largely unexplored. To the best of our knowledge, this is the first study to investigate scaling behavior in stablecoin transaction data, focusing on USDT and USDC. We analyze approximately 370 million USDT and USDC transactions recorded on the Ethereum blockchain across six periods spanning June 2024 to February 2026. Based on interactions between Externally Owned Accounts (EOAs) and Smart Contracts (SCs), we classify transactions into four categories: EOA-EOA, EOA-SC, SC-EOA, and SC-SC. Using maximum-likelihood estimation of power-law exponents, we find that transaction value distributions exhibit heavy-tailed scaling for both stablecoins across all periods and interaction categories. We identify two distinct scaling regimes: EOA-involved categories cluster around 1.45-1.60, whereas SC-SC transactions exhibit higher exponents of approximately 1.72-1.73. Sensitivity analysis confirms that this separation is robust across periods, stablecoins, and fitting sample sizes. Counterfactual analysis shows that changes in category weights alone cannot explain the observed variation in the overall exponent. Across different sample sizes, the counterfactual path accounts for only about 10%-35% of the total temporal range observed in the actual data. Overall, our results indicate two broadly differentiated scaling regimes in the tail of stablecoin transaction values. Power-law tail behavior is observed throughout stablecoin transaction activity, but the exponent depends on whether transactions are driven by EOAs or SCs. These findings provide a basis for further research on scaling behavior and transaction heterogeneity in blockchain-based financial systems.