Follow blockchain research across journals, conferences, and preprint repositories.
97,057 results · page 349 of 4,045
J. Y. Lin, Hui Li, Min Wang, Niansheng Tang · 10 authors
No abstract is available for this record.
Yuqiu Zhang, Hans-Arno Jacobsen
Serverless computing promises on-demand elasticity and simplified deployment, yet today's production-grade serverless platforms remain tied to a single-provider, centrally scheduled control plane. This centralized scheduling model faces mounting challenges in handling heterogeneous policies, data governance constraints, and dynamic workloads for the modern web, where applications increasingly span multiple geo-distributed autonomous administrative domains. In this paper, we present Mocha, a decentralized, policy-aware framework for scheduling serverless functions across a federated ecosystem. At its core, Mocha proposes a hierarchically structured distributed hash table that embeds geographical and organizational context to facilitate locality-aware scheduling without any central authority. By implementing a formally specified compliance engine at each domain, Mocha guarantees that all regulatory, locality, and resource constraints are honored for function placement decisions. Experiments show that Mocha reduces scheduling tail latency by 4–9× compared to alternatives while maintaining full policy adherence.
Aleksi Heikkilä
The aim of this bachelor’s thesis is to clarify the key similarities and differences between physical and virtual real estate markets, focusing on marketplaces, transaction processes, market participants and value formation. The study is conducted as a literature review comparing the established, nationally regulated practices of traditional real estate markets with the global and still developing structure of blockchain-based metaverse markets. The findings show that although both markets share fundamental value drivers such as location, scarcity and income potential, the mechanisms behind these factors differ significantly. Institutional investors play a stabilizing role in physical markets, whereas metaverse markets remain fragmented and speculative. The results complement existing research and provide practical insights for professionals in both real estate and Web3 environments.
Matthieu Pigaglio, Onur Ascigil, Michał Król, Felix Lange · 9 authors
Layer-2 protocols such as rollups can help address Ethereum's throughput limits. An efficient data availability layer is key for layer-2 support in Ethereum, but broadcast methods do not scale. A promising approach is the selective distribution of layer-2 data and its verification by data availability sampling (DAS). Integrating DAS with Ethereum consensus is, however, a challenge, as data must be shared and sampled within 4 seconds of each consensus slot.
Yan Wu, Cong Wu, Yebo Feng, Lin Li · 12 authors
As cryptocurrency prices continue to recover, crypto crimes such as money laundering are becoming increasingly rampant. Mixing services such as Tornado Cash have become the primary tools for obfuscating illegal financial transactions due to their inherent anonymity mechanisms. Tornado Cash is a non-custodial, smart contract-based mixing service (SC-CMS) that breaks the direct mapping between deposit and withdrawal accounts, hindering regulators from tracking illicit fund flows. Existing deanonymization methods for Tornado Cash suffer from several challenges, including vague theoretical concepts, evolving mixing mechanisms, and insufficient labeled samples. To address these concerns, this paper proposes the first formal concept of SC-CMS to facilitate and evaluate the deanonymization efforts systematically. We design a novel linkability attack, LASC, based on enhanced graph structure learning, to associate mixing accounts on Tornado Cash and mathematically prove its feasibility. Comprehensive experiments on real Ethereum transactions demonstrate that LASC outperforms state-of-the-art works in both performance and efficiency.
Felix Bekemeier, Fabian Schär, Hato Schmeiser
This paper presents a model in which risk-averse individuals can purchase insurance via traditional indemnity contracts or Decentralized Finance (DeFi) smart contract-based instruments. The model incorporates key features of DeFi insurance, including parametric payouts, basis risk arising from imperfect loss verification and pooled collateralization involving the risk of liquidity shortfalls. We characterize optimal insurance choices as a function of pricing, payout correlation and risk preferences. Numerical results show that DeFi insurance can complement or replace traditional coverage, improving welfare when basis and default risks are moderate or pricing advantages are substantial. The analysis reveals how DeFi-specific frictions shape insurance demand and provides insight into how DeFi instruments may shift market structure and expand the set of attainable risk transfer outcomes.
Xiaoqi Li, Hailu Kuang, Wenkai Li, Zongwei Li · 5 authors
Traditional approaches for smart contract analysis often rely on intermediate representations such as abstract syntax trees, control-flow graphs, or static single assignment form. However, these methods face limitations in capturing both semantic structures and control logic. Knowledge graphs, by contrast, offer a structured representation of entities and relations, enabling richer intermediate abstractions of contract code and supporting the use of graph query languages to identify rule-violating elements. This paper presents CKG-LLM, a framework for detecting access-control vulnerabilities in smart contracts. Leveraging the reasoning and code generation capabilities of large language models, CKG-LLM translates natural-language vulnerability patterns into executable queries over contract knowledge graphs to automatically locate vulnerable code elements. Experimental evaluation demonstrates that CKG-LLM achieves superior performance in detecting access-control vulnerabilities compared to existing tools. Finally, we discuss potential extensions of CKG-LLM as part of future research directions.
Abubakar Ibrahim Adamu, Hamidu Ardo, Najaatu Mohammed Bomai
The aim of this research is to analyze the cryptocurrency from Islamic Perspective. Cryptocurrency is a new phenomenon to Islamic Law. It is a digital currency that is neither issued by a central bank nor a public authority, but accepted as a medium of exchange by some individuals and entities and can be transferred, stored or traded electronically. Its legal nature remains unclear some are considering it as only medium of exchange while others as commodity, couple with some of its peculiar features such as anonymity of transacting parties, lack of control and supervision by a central authority, intangibility and speculation. The paper begins with brief introduction on the Islamic law principles governing commercial transactions. The paper continues with the explanation of the concept, nature and scope of cryptocurrency from Islamic Perspective. Analytical research methodology is used to analyze the work. At the end it is observed that contemporary Muslims scholars differ as to the position of cryptocurrency in Sharia. Some look at it as halal (permissible) in principle, while others look at it as haram (prohibited). However, the research recommends that a further research need to be conducted as to the actual legal status of cryptocurrency and its impact in both social and economic life of Muslims, this will assist in making a final decision on it.
Vipul Goyal, Xiao Liang, Omkant Pandey, Yuhao Tang · 5 authors
No abstract is available for this record.
Shihui Fu
No abstract is available for this record.
Tharun Tejavath, Surendra Srinivas, A Vamshi
This paper presents a blockchain-based smart pricing framework designed to enhance traditional electricity markets by enabling decentralized, peer-to-peer (P2P) energy trading among distributed renewable energy producers and consumers. The proposed system, implemented on the Ethereum blockchain, introduces SmartPricingExchange. The system employs energy credits managed through an internal ledger to facilitate transparent and automated transactions. By removing conventional intermediaries such as DISCOMs, the framework promotes market liberalization, improves price transparency, and incentivizes small-scale producers through fair and trustless settlements. Deployed on the Ethereum Sepolia testnet using Remix IDE and MetaMask, the model demonstrates the feasibility of decentralized energy exchange and offers a scalable path for the modernization of future power markets.
Xingyi Li, Zhuang Liu, Yujun Liu, Shushang Zhu · 5 authors
We investigate the predictability of cryptocurrency returns using a comprehensive set of macroeconomic and cryptocurrency-specific factors and a set of 12 machine learning models. To enhance interpretability, we employ SHAP analysis to quantify the marginal contribution of each factor to model outputs. We further assess the economic value of predictive signals by constructing long-short and long-only portfolios. Empirically, tree-based methods, particularly random forests, deliver the highest predictive accuracy and outperform neural network and linear benchmarks, with predictability substantially stronger than that documented in equity markets. Across models, the market-to-realized-value ratio, new addresses, and active addresses consistently emerge as the most influential predictors, with higher values associated with higher expected returns. Portfolio results show that neural network-based strategies achieve the highest cumulative performance, indicating meaningful investment gains. Overall, our findings demonstrate the value of machine learning for return forecasting in the cryptocurrency market and provide practical insights for investors and financial analysts operating in highly volatile and evolving cryptocurrency environments.
Ece Kozol
No abstract is available for this record.
Hong-Sen Yang, Qun-Xiong Zheng, Jing Yang
No abstract is available for this record.
Zhe Li, Chaoping Xing, Yizhou Yao, Chen Yuan · 5 authors
No abstract is available for this record.
Mingshu Cong, Sherman S. M. Chow, Siu Ming Yiu, Tsz Hon Yuen
No abstract is available for this record.
Nam Tran, Khoa Nguyen, Dongxi Liu, Josef Pieprzyk · 5 authors
No abstract is available for this record.
T.Pandiselvi
The rapid evolution of cyber threats has exposed fundamental weaknesses in traditional intrusion detection systems, particularly those dependent on centralized architectures vulnerable to data tampering, single-point failures, and delayed threat response. As organizations face increasingly sophisticated attacks, a resilient and transparent framework for detecting and validating abnormal activity has become essential. This study examines the design and effectiveness of a blockchain-based intrusion detection system (BIDS) that leverages distributed consensus, immutable logging, and cooperative threat intelligence to enhance the reliability and responsiveness of security operations. By integrating blockchain technology with anomaly-based and signature-based identification methods, the proposed model establishes a secure environment where intrusion data cannot be altered, suppressed, or manipulated by internal or external adversaries. Through experimental evaluation across simulated network environments, the blockchain-enabled detection model demonstrates significant improvements in event accuracy, traceability, and coordination between participating nodes. The decentralized ledger structure ensures that alerts are validated collectively, reducing false positives and limiting the adversary’s ability to compromise the detection process. The integrity of recorded events also enhances forensic analysis, allowing security teams to reconstruct attack sequences with greater confidence. Additionally, the study reveals that the distributed nature of the system provides high fault tolerance, enabling continuous operation even under attempted denial-of-service conditions or node outages. Performance analysis indicates that blockchain integration does introduce additional computational overhead; however, the trade-off is compensated by the increased transparency, data authenticity, and resistance to insider threats that the system delivers. The research further highlights that smart contracts can automate rule enforcement and improve response mechanisms by triggering protective actions when predefined thresholds are met. This automation contributes to shortening detection-to-response timelines, a critical factor in mitigating fast-moving cyberattacks. Overall, the findings suggest that blockchain-powered intrusion detection represents a promising direction for strengthening network security in decentralized, cloud-based, and large-scale enterprise environments. By combining autonomous threat identification with tamper-proof logging and distributed validation, the proposed approach offers a comprehensive pathway for defending modern digital infrastructures against evolving cyber risks. The study concludes that integrating blockchain technology with intrusion detection principles not only reinforces system resilience but also lays the groundwork for more collaborative, transparent, and secure cybersecurity ecosystems.
Thomas den Hollander, Daniel Slamanig
No abstract is available for this record.
K. C. Yang, W. P. Chao, Cm Shih, C.C. Kao · 5 authors
With the rapid advancement of technology in the financial sector, financial technology (FinTech) has become a major focus of industry development. Among its various branches, insurance technology (InsurTech) has emerged as a particularly prominent and widely discussed topic in recent years. By leveraging innovative technologies such as artificial intelligence (AI) and blockchain, insurance processes can be automated to enhance service efficiency while maintaining data integrity. This study proposes a business model based on blockchain technology and implements an insurance system using Ethereum smart contracts to support the purchase of flight delay insurance and automate the claims process. The system ensures the integrity of both policy information and transaction records. To determine flight delays, it utilizes the Open API provided by the Transportation Data eXchange (TDX) of Taiwan’s Ministry of Transportation. This integration aligns with the core principles of insurtech, particularly in promoting data sharing and interoperability in system development.
Shai Levin, Robi Pedersen
No abstract is available for this record.
Peng, Zifan, Zheng, Jingyi, Liu, Yule, Jia, Huaiyu · 11 authors
Understanding the economic intent of Ethereum transactions is critical for user safety, yet current tools expose only raw on-chain data or surface-level intent, leading to widespread "blind signing" (approving transactions without understanding them). Through interviews with 16 Web3 users, we find that effective explanations should be structured, risk-aware, and grounded at the token-flow level. Motivated by these findings, we formulate TxSum, a new user-centered NLP task for Ethereum transaction understanding, and construct a dataset of 187 complex Ethereum transactions annotated with transaction-level summaries and token flow-level semantic labels. We further introduce MATEX, a grounded multi-agent framework for high-stakes transaction explanation. It selectively retrieves external knowledge under uncertainty and audits explanations against raw traces to improve token-flow-level factual consistency. MATEX achieves the strongest overall explanation quality, especially on micro-level factuality and intent quality. It improves user comprehension on complex transactions from 52.9% to 76.5% over the strongest baseline and raises malicious-transaction rejection from 36.0% to 88.0%, while maintaining a low false-rejection rate on benign transactions.
Jens Groth, Harjasleen Malvai, Andrew Miller, Yi-Nuo Zhang
No abstract is available for this record.
Harshit Rathor, Sakshi Kathuria
The study is grounded on the significant shifts, central values, and increased influence of Blockchain Technology on the industries. It addresses Blockchain Technology starting theoretically as a cryptographic concept of the beginning through to its contribution as a primarycomponent of decentralized computing (Web3). The discussion begins as the key issues are examined, namely, decentralized agreement, cryptographic hashing, and immutability. Such subjects enable the Blockchain Technology to gain trust in cases where mediators were being used in the past. Moreover, the research considers the impacts of Blockchain Technology on such critical industries as Decentralized Finance (DeFi), supply chain management, and decentralized governance (DAOs).