Blockchain Papers

Davide Sandretto

No abstract is available for this record.

FilipLevý

The bachelor’s thesis Institutional Arrangement of Cryptocurrencies primarily focuses on issues related to individual cryptocurrencies, cryptocurrency exchanges, and their regulation. Its aim is to compare individual cryptocurrency exchanges and the regulation of trading in these currencies across different countries. The first chapter defines cryptocurrencies and discusses individual digital currencies and the technologies on which they operate. The second chapter deals with cryptocurrency trading, focusing on exchanges and their comparison. The third chapter addresses regulation, particularly its forms, as well as regulation at the level of individual states and their comparison.

Aditya Gupta, Vibha Jain

ABSTRACT The perishable food cold chain is a vital part of the global food system, mainly ensuring the quality of temperature‐sensitive products such as milk, seafood, fruits, and vegetables. However, this system still faces several challenges related to real‐time monitoring, data transparency, and proactive demand planning, which often lead to spoilage, food safety violations, and disruptions. In this work, we propose a comprehensive end‐to‐end system that includes Internet of Things (IoT)‐based environmental sensors, blockchain‐enabled immutable logging, and a hybrid ARIMA–LSTM model for demand forecasting and spoilage risk detection. The system uses ESP32 microcontrollers with DHT11 sensors at key cold‐chain points to collect temperature and humidity data, streamed to Blynk dashboards for real‐time visualization and anomaly alerts. Anomalies and product metadata are permanently recorded through smart contracts on a private Ethereum blockchain, while payloads are stored off‐chain on IPFS for traceability and auditability. Additionally, historical blockchain logs and external sales data are used to train a hybrid ARIMA–LSTM model that predicts future demand and spoilage risks more accurately. Experimental results show that the proposed model achieves a forecasting accuracy of 90% ( R 2 = 0.90), outperforming baseline approaches on multiple metrics including RMSE, MAE, MAPE, and R 2 . The framework is scalable and data‐driven, aiming to improve supply availability and reduce food waste.

Boon Chuan Lim

No abstract is available for this record.

Robin Schattmann

No abstract is available for this record.

Dmitry E. Petrov

The article is devoted to the study of the possibilities of applying blockchain technology in the system of intellectual property management in the context of the digital economy. The limitations of the traditional rights registration model are examined, and the potential of distributed ledgers for recording authorship, automating royalty payments, and increasing transparency in the circulation of rights is substantiated. The advantages and risks of implementing blockchain solutions are analyzed, as well as the prospects for developing hybrid models involving state registries.

Hugo Muñoz Ureña

No abstract is available for this record.

Saeed Ahmadi

No abstract is available for this record.

Maxat Kassen

No abstract is available for this record.

Prof. M. A. Sayyad, Veerendra Yadav, Dr. Geetika M. Patel, Dr. Prakash Deep · 8 authors

The problem of data privacy, interoperability, cyberattacks, and unauthorized changes of sensitive medical records are becoming critical issues in healthcare information exchange systems. The conventional centralized healthcare designs have single-point failures, inadequate transparency, sluggish data synchronization, and insufficient trust management among dispersed medical organizations. In order to overcome these shortcomings, this paper suggests a Blockchain-Assisted Distributed Artificial Intelligence Framework to Secure Healthcare Information Exchange and Data Integrity. The suggested architecture combines a distributed AI-based healthcare analytics system with blockchain-based immutable ledger systems to provide secure, open, and alteration-free medical data exchange among various healthcare nodes. The automated access control and the secure management of authorization is applied using smart contracts, and intelligent anomaly detection and integrity verification of healthcare transactions are implemented using distributed AI modules. The framework also includes encrypted communication and decentralized consensus systems to promote security and reliability in the context of multi-institutional healthcare settings. Simulated healthcare data based on experimentation shows that the proposed framework has a data integrity verification accuracy of 96.4, anomaly detection accuracy of 92.7 and offers both efficient and secure transaction validation performance at a ratio of 41.3 lower than traditional centralized healthcare systems. The suggested architecture enhances the security of healthcare data and trust management, scalability and interoperability of the next-generation intelligent healthcare ecosystems significantly.

Maria-Teresa Paracampo

This paper examines the various steps taken toward the tokenization of finance, made possible by distributed ledger technology (DLT), in the European and national contexts. In a context favourable to innovation and the use of enabling technologies, as outlined in the EU Strategy for Digital Finance, the European Commission is taking action on two complementary fronts that leverage the benefits of DLT: one focused on crypto-asset markets (MICA Regulation), the other relating to crypto-assets that qualify as financial instruments (Pilot Regime Regulation). The adoption of the sandbox model allows for the testing of DLT at both European and national level, where the adoption of the so-called FinTech Decree goes beyond the scope outlined by the EU Regulation to establish a legislative framework supporting the issuing and circulation of financial instruments in digital form via distributed ledger technologies. Despite the first instances of use and experiences in Italy, the current situation reveals a market still in the exploratory phase, hampered by the temporary nature typical of experimentation, but above all awaiting European action to establish a lasting framework for DLT.

Hani Al-Balasmeh

No abstract is available for this record.

Mojtaba Khalili

Quasi-adaptive non-interactive zero-knowledge (QA-NIZK) arguments are fundamental cryptographic primitives widely used in privacy-preserving technologies such as anonymous credentials, group signatures, e-cash, and blockchain-based applications. We present the first tightly secure unbounded simulation sound quasi-adaptive non-interactive zero-knowledge argument system from simple assumptions. The construction has a security loss ofO(1), a compact common reference string, constant size proofs, and its security relies on the hardness of the well-known SXDH assumption. Our result improves state-of-the-art (Couteau and Hartmann, CRYPTO 2020) in terms of the proof size (about three times), a lower security loss, and also with respect to the underlying hardness assumptions. The tight security reduction enables shorter key-length recommendations, leading to improved concrete efficiency. Our main technical contribution is a novel proof technique inspired by the randomization technique of the Naor-Yung double-encryption paradigm and the adaptive partitioning due to Hofheinz (EUROCRYPT 2017).

CS Chai

No abstract is available for this record.

Dikshant Agarwal

No abstract is available for this record.

Ali Şah Özcan, Cihangir Tezcan, Erkay Savaş

No abstract is available for this record.

Lanyi Wang

In recent years, decentralized networks have increasingly relied on secure and efficient data exchange systems to support large-scale operations and collaborative processes. Traditional centralized systems face challenges in scalability, transparency, and trust management, which blockchain technology can address. However, existing research has primarily focused on data integrity and static trust models, neglecting dynamic trust propagation, privacy concerns, and the interpretability of trust-related decisions. This study proposes a blockchain-driven information system that integrates a Trust Score Aggregation Module (TSAM), a Hybrid Consensus Protocol (HCP), and a Privacy-Preserving Smart Contract Framework (PPSCF) to address these gaps. The TSAM enables dynamic trust propagation, while the HCP optimizes communication efficiency, and the PPSCF ensures privacy through zero-knowledge proofs. Experimental results show that the proposed system reduces latency by 27.3 % (0.98±0.07 s), increases throughput by 27.1 % (140±6 tps), and achieves a 33.3 % reduction in trust variance compared to baseline systems. The system also improves interpretability by 22.0 %, maintaining low privacy overhead (5.1±0.8 %). This research advances the understanding of blockchain-based trust management in decentralized environments, providing a scalable, interpretable, and privacy-preserving framework that can be applied across various domains and operational scales. The proposed methodology lays a foundation for future blockchain applications in large-scale systems, particularly in environments requiring robust data governance and compliance.

Quoc Khanh Huynh, Nhat Nguyen Nguyen, Tuan-Dung Tran

No abstract is available for this record.

M. Sreelakshmi, Shaik Naseera

No abstract is available for this record.

Zhiqiang Zhang, Youwen Zhu, Xiaodong Yang, Xiaohui Ding · 7 authors

Attribute-Based Encryption (ABE) enables fine-grained access control over outsourced data, but its key generation process typically requires users to disclose their complete attribute sets, introducing significant privacy risks. Existing privacy-preserving approaches—such as those based on zero-knowledge proofs or tightly coupled interactive protocols—suffer from limited scalability, high communication costs, and insufficient support for selective attribute disclosure. To address these limitations, we propose a privacy-enhancing key generation protocol guided by the principle ofMinimal Disclosure, which ensures that users disclose only the minimally necessary subset of attributes required for authorization. Our protocol decouples attribute verification from key issuance: users first obtain cryptographically verifiable attribute tokens, and later issue blinded key requests over selectively chosen attributes. This design enables selective disclosure, supports reusable attribute credentials, and enhances user autonomy. To improve scalability, we introduce a lightweight batch verification mechanism that reduces computation and communication overhead for the attribute authority. We prove that our protocol achieves thebindingandhidingproperties under standard cryptographic assumptions, and we formally verify these guarantees in the symbolic model using the ProVerif tool. In addition, we propose two privacy metrics—AttributeInference Gain (AIG) andPrivacy Gain (PG)—alongside an entropy-based analysis to quantify resistance against attribute inference attacks. Experimental results show that our scheme effectively mitigates inference leakage while offering substantial efficiency gains compared to existing schemes.

David Krause

No abstract is available for this record.

David Krause

No abstract is available for this record.

Vanessa Villanueva Collao

No abstract is available for this record.

Shreyas Kamble

No abstract is available for this record.