Blockchain Papers

L. Naveenkumar, S H Manjula

No abstract is available for this record.

Mohini Verma, Mohona Ghosh, Amar Kumar Mohapatra

No abstract is available for this record.

Daniel Ferreira

ABSTRACT Research Question/Issue Blockchain technology promises to revolutionize governance through strong commitments, trustlessness, and transparency. This paper examines how these promises have failed to materialize in practice. Research Findings/Insights Drawing on case evidence from major blockchains, including Bitcoin and Ethereum, I argue that blockchains have evolved into technocracies where developers, foundations, and companies exercise disproportionate control. Rather than being exceptional, blockchain governance suffers from the same coordination problems, collective action failures, and centralization tendencies that plague traditional governance systems. Theoretical/Academic Implications The paper concludes that while blockchains offer valuable experiments in governance design, their alleged advantages over traditional institutions remain largely mythical. Practitioner/Policy Implications Blockchain organizations should acknowledge their reliance on off‐chain coordination and informal authority. Investors must understand that blockchain governance depends on trusting technical elites, while regulators should recognize that decentralization claims often mask concentrated power structures requiring traditional oversight.

Akmam Majed Mosa

Decentralized finance (DeFi) protocols are becoming increasingly targeted by cyber threats, such as liquidity drain attacks, smart contracts flaws that leverage instant loans, and increasingly sophisticated threats that include DarkGate ransomware. We develop a hybrid framework that integrates CTI and predictive analytics to facilitate improving consensus mechanisms in a blockchain network. The proposed framework is centered on three layers , a data collection and processing layer, a security oracle layer that engages to mitigate intervention, and a dynamic adaptive mechanism to reach consensus. A 250-node testbed was built and deployed with the Hyperledger Besu and Geth deployments of Ethereum incorporating hybrid GRU-BiLSTM which utilize GNN's for predicting attacks. The results reveal improvements of transaction processing TPS of up to +236%, settlement latency improved -75%, fork rate improved to less than 3%, and downtime improved from 15% to 1.5%. Statistical tests T-Test and ANOVA also reveal these were of high statistically significance at p < 0.01. This study emphasizes that bridging functional aspects of AI with adaptive consensus mechanisms will be an effective approach at combating advanced cyber-attacks while maintaining reliability and resilience in DeFi systems.

Sani Lawal

The convergence of blockchain and Zero Trust Architecture (ZTA) offers a transformative pathway for enhancing security and resilience in financial infrastructures. Traditional network perimeter models are increasingly inadequate for safeguarding decentralized finance (DeFi), payment systems, and digital asset platforms that operate across distributed environments. This study explores how Zero Trust principles rooted in continuous verification, least privilege access, and micro-segmentation can be effectively integrated into blockchain ecosystems to mitigate identity spoofing, insider threats, and data tampering. By examining hybrid frameworks that combine permissioned blockchains with Zero Trust access controls, the research highlights a paradigm shift toward adaptive, identity-centric security postures in financial networks. The proposed model emphasizes dynamic authentication, real-time monitoring, and cryptographic assurance to ensure trustless yet verifiable interactions among nodes and participants. This integration not only fortifies compliance with emerging regulatory standards but also enhances interoperability and transparency across multi-chain financial systems. The findings suggest that embedding Zero Trust principles within blockchain-oriented infrastructures can create a self-healing, auditable, and future-ready digital finance ecosystem.

Idris Olanrewaju Ibraheem, Abdulrauf Tosho, Kamil Saka, Bolakale Lawal Aremu

Blockchain technology has revolutionized digital transactions by offering decentralization, transparency, and immutability. However, its inherent transparency often conflicts with the need for user privacy and anonymity, raising significant concerns regarding accountability, especially in regulatory and legal contexts. This study explores the delicate balance between anonymity and accountability in blockchain systems, proposing a framework that ensures both privacy and compliance with regulatory requirements. The research addresses key challenges in balancing these two aspects, evaluates the effectiveness of existing privacy-preserving technologies such as zero-knowledge proofs and ring signatures, and introduces the Privacy-Accountability Balanced Blockchain (PABB) Framework. This framework integrates Selective De-Anonymization, Self-Sovereign Identity (SSI), and the Adaptive Privacy-Accountability Control (APAC) Algorithm to dynamically adjust privacy levels based on regulatory conditions. Through theoretical analysis, mathematical modeling, and empirical validation, preserving privacy for 92% of transactions while enabling selective de-anonymization in high-risk cases, the study demonstrates that the APAC Algorithm effectively balances privacy and compliance needs. The findings suggest that privacy-conscious blockchain systems can coexist with accountability mechanisms, paving the way for ethical and legally sound blockchain applications. The study concludes that the PABB Framework offers a practical and scalable approach to achieving this balance, fostering trust among users and regulators alike.

Amirreza Samari, Parsa Hedayatnia, Seyyed Javad Bozorgzadeh Razavi, Mohammad Allahbakhsh · 5 authors

Smart contracts play a pivotal role in decentralized applications but are subject to security vulnerabilities often difficult to detect. Traditional static and symbolic analysis tools cannot handle intricate logic and are limited in adaptability and explainability. Recent development of large language models (LLMs) provide new opportunities for vulnerability detection, but single-model methods often suffer from inconsistency and prompt sensitivity. This paper introduces a collaborative LLM-based model that enhances detection robustness through semantic similarity-based few-shot prompting and multi-LLM reasoning. Our model integrates diverse LLMs (ChatGPT, Gemini, Grok) as worker nodes, along with an aggregator model to resolve disagreements via justification analysis and final prediction consolidation. Experimental evaluations on the SmartBugs benchmark demonstrated a remarkable enhancement in detection accuracy (96.25%) and response time compared to other models. The proposed model provides a scalable and explainable solution for smart contract auditing, illustrating the strength of LLM collaboration in security-critical applications.

Manaswini Bollikonda

The rapid expansion of multi-cloud ecosystems has intensified the demand for privacy-preserving analytics across untrusted infrastructures. This paper proposes Federated Zero-Trust Analytics (FZTA), a framework that integrates federated learning, zero-trust security, and privacy-enhancing computation to enable secure data collaboration without centralized trust. The design combines continuous identity verification, decentralized policy enforcement, and hybrid cryptography based on homomorphic encryption and differential privacy. Evaluation across three commercial clouds demonstrates that FZTA achieves near baseline model accuracy (within 2% of centralized training) while maintaining (ε<1.2, δ=10−5) differential privacy guarantees and less than 20% computational overhead. The framework resists eavesdropping, replay, and model inversion attacks while meeting compliance standards such as GDPR and HIPAA. Results confirm that strong privacy and federated scalability can coexist under zero-trust conditions, establishing a foundation for secure cross-domain analytics in healthcare, finance, and IoT applications.

Sonali B. Wankhede, Dhiren Patel

Internet of Things (IoT) is transforming traditional agriculture into a more efficient, sustainable, and data-driven industry. By connecting various devices and sensors across the farm, IoT enables real-time monitoring, control, and optimization of agricultural processes. However, there are many security issues to deal with. IoT devices in precision farming collect sensitive data such as soil moisture, nutrient levels, and livestock health information. Unauthorized access to farm data can result in data theft, manipulation, or misuse. This can compromise the integrity of farming operations and potentially harm the environment. In this paper, we explore the mathematical foundations and practical implementations of model aggregation in federated learning (FL), with a particular focus on integration with distributed ledger technologies (DLT). We present a comprehensive analysis of aggregation algorithms, their convergence properties, and security guarantees. Additionally, we survey existing tools and platforms that facilitate federated learning deployments and examine how blockchain technology can address key challenges in federated learning systems including trust, incentive mechanisms, and auditability. Our analysis demonstrates that the combination of federated learning with blockchain creates a robust, transparent, and decentralized machine learning systems suitable for privacy-sensitive applications across precision farming, healthcare etc.

Легенько, В. Ю.

The article is devoted to the study of the current legal regulation of virtual assets in the Federal Republic of Germany. The author analyses the advantages and disadvantages of the relevant regulatory framework, decisions taken to harmonise legislation in accordance with the new Regulation of the European Parliament and of the Council, as well as the possibility and expediency of implementing the most successful decisions into Ukrainian legislation. Due to the lack of relevant in-depth studies that would combine the main regulatory norms and definitions, as well as provide a general overview of this regulatory system, it became necessary to conduct a detailed study of the current regulatory framework of the Federal Republic of Germany in this area, which is one of the most complex among known jurisdictions in the field of virtual assets. The following list details the responsible regulators, as well as the legally established definition of virtual assets and their classification. The Federal Republic of Germany has developed an original classification system and a hybrid approach to defining asset categories in order to apply the provisions of MiCA. Currently, not all objects created on the basis of blockchain technology are subject to regulation, primarily non-fungible tokens, which is in line with MiCA provisions. The licensing system for service providers in the field of virtual asset circulation, the specifics of the transition period and the new classification of licence classes in accordance with MiCA were also examined. An analysis of the requirements for initial coin offerings (ICOs) in accordance with the regulatory framework of the Federal Republic of Germany and MiCA was conducted. The issues of virtual asset mining regulation and taxation were examined. It is concluded that the Federal Republic of Germany has found a way to regulate many more assets than provided for by MiCA, which gives competitive advantages to the national economy. Ukrainian legislation needs to borrow the approach to building such a regulatory system, which can be harmonised with European Union legislation, while preserving the advantages of its own legislation.

V. I. Lehenko

The article is devoted to the study of the current legal regulation of virtual assets in the Federal Republic of Germany. The author analyses the advantages and disadvantages of the relevant regulatory framework, decisions taken to harmonise legislation in accordance with the new Regulation of the European Parliament and of the Council, as well as the possibility and expediency of implementing the most successful decisions into Ukrainian legislation. Due to the lack of relevant in-depth studies that would combine the main regulatory norms and definitions, as well as provide a general overview of this regulatory system, it became necessary to conduct a detailed study of the current regulatory framework of the Federal Republic of Germany in this area, which is one of the most complex among known jurisdictions in the field of virtual assets. The following list details the responsible regulators, as well as the legally established definition of virtual assets and their classification. The Federal Republic of Germany has developed an original classification system and a hybrid approach to defining asset categories in order to apply the provisions of MiCA. Currently, not all objects created on the basis of blockchain technology are subject to regulation, primarily non-fungible tokens, which is in line with MiCA provisions. The licensing system for service providers in the field of virtual asset circulation, the specifics of the transition period and the new classification of licence classes in accordance with MiCA were also examined. An analysis of the requirements for initial coin offerings (ICOs) in accordance with the regulatory framework of the Federal Republic of Germany and MiCA was conducted. The issues of virtual asset mining regulation and taxation were examined. It is concluded that the Federal Republic of Germany has found a way to regulate many more assets than provided for by MiCA, which gives competitive advantages to the national economy. Ukrainian legislation needs to borrow the approach to building such a regulatory system, which can be harmonised with European Union legislation, while preserving the advantages of its own legislation.

Nikhil Sharma, Prashant Giridhar Shambharkar

No abstract is available for this record.

Behnam Khayer, Siamak Mirzaei, Hooman Alavizadeh, Ahmad Salehi Shahraki

Blockchain technologies offer transformative potential in terms of addressing the security, trust, and identity management issues that exist in large-scale Internet of Things (IoT) deployments. This narrative review provides a comprehensive survey of various studies, focusing on decentralized identity management, trust mechanisms, smart contracts, privacy preservation, and real-world IoT applications. According to the literature, blockchain-based solutions provide robust authentication through mechanisms such as Physical Unclonable Functions (PUFs), enhance transparency via smart contract-enabled reputation systems, and significantly mitigate vulnerabilities, including single points of failure and Sybil attacks. Smart contracts enable secure interactions by automating resource allocation, access control, and verification. Cryptographic tools, including zero-knowledge proofs (ZKPs), proxy re-encryption, and Merkle trees, further improve data privacy and device integrity. Despite these advantages, challenges persist in areas such as scalability, regulatory and compliance issues, privacy and security concerns, resource constraints, and interoperability. By reviewing the current state-of-the-art literature, this review emphasizes the importance of establishing standardized protocols, performance benchmarks, and robust regulatory frameworks to achieve scalable and secure blockchain-integrated IoT solutions, and provides emerging trends and future research directions for the integration of blockchain technology into the IoT ecosystem.

Junyi Wen, Wuhui Chen, Jianting Zhang, Xiao Chen · 7 authors

The Execute-Order-Validate (EOV) framework has been used to improve the scalability of blockchains by concurrently executing transactions. However, the EOV framework also poses a critical performance issue. Specifically, when multiple transactions access the same data, only one of them can be committed eventually while the others are aborted due to the strong concurrency control restriction. This inefficiency makes the EOV framework far from practicality since there always exist hotspot variables that can be frequently accessed in real-world scenarios, such as the Fungible Token (FT) and Non-Fungible Token (NFT) online marketplace. In this paper, we propose RapidSnail, a novel EOV framework that enables transactions to execute based on the uncommitted data to reduce the transaction abort rate in such scenarios with hotspot variables. We first propose a new read-write set representation and a concurrency execution schedule algorithm in the execution phase to maintain the concurrent efficiency. Then we propose an effect-based conflict graph construction algorithm in the order phase to handle the conflict transactions based on the new read-write set. Finally, we propose a concurrent commitment schedule algorithm to adopt the new read-write set to validate the transactions concurrently in the validation phase. Our experiment results show that RapidSnail increases the throughput by at least 4× compared to the state-of-the-art EOV framework under high contention workload. More specifically, RapidSnail reduces the abort rate by 50%, and achieves at least 4× speedup in the order phase and 2.94× speedup in the validation phase over the existing EOV frameworks.

Bowen He, Yufeng Hu, Zhuo Chen, Yuan Chen · 8 authors

The prosperity of Ethereum gives rise to a new type of transaction-based phishing scam. Specifically, users are tempted to visit phishing websites and sign phishing transactions that allow scammers to withdraw their tokens. Meanwhile, to accelerate the deployment of phishing websites, scammers have introduced a business model, Drainer-as-a-Service (DaaS). In this model, drainer operators focus on crafting specialized phishing toolkits, named ''wallet drainers'', while drainer affiliates handle the deployment and promotion of phishing websites. After stealing victims' tokens, they will distribute profits. In this paper, we present the first systematic study of DaaS on Ethereum. To begin with, we propose a snowball sampling approach to build the first large-scale DaaS dataset, including 1,910 profit sharing contracts, 56 operator accounts, 6,087 affiliate accounts, and 87,077 profit-sharing transactions. Then, we analyze the scale of DaaS from the perspectives of victims, operators, and affiliates, and perform clustering analysis to uncover dominant DaaS families. Finally, we reported DaaS accounts in the dataset and 32,819 phishing websites deployed with DaaS toolkits to the community. Our work aims to serve as a guide for Ethereum service providers to enhance user protection against DaaS.

Saenko, Elena

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Digital Transformation

Ashish Verma, Akhil Sharma, Akanksha Sharma, Sunita Sunita · 6 authors

Blockchain is rapidly developing in many sectors, and it is promising its application specifically for healthcare. This chapter examines the potential of blockchain technology to offer solutions to some of the key problems in healthcare systems, including data breaches, fragmented systems, and the apparent lack of patient control over their health records, all of which could be addressed through the use of secure and transparent blockchain systems. With its sophisticated encryption technology, consensus algorithms, and decentralised access control, Blockchain is well-suited to securing sensitive healthcare data. The chapter explores the technical architecture of Blockchain in healthcare, contrasting public and private blockchains and looking at the role of consensus mechanisms such as proof-of-stake and proof-ofauthority. Some critical healthcare-based applications are the management of secure patient data, the management of the drug supply chain, clinical trials, and medical billing, in which Blockchain helps keep the data integrity, fraud prevention, and compliance assurance. Despite its promising benefits, challenges such as scalability, high implementation costs, and resistance to change within the healthcare ecosystem are discussed as well. By addressing these limitations, Blockchain can significantly improve the security and transparency of healthcare systems.

Adrian Leonard Mociulschi

This article examines blockchain governance as a cultural and algorithmic paradigm, moving beyond code to constitutional logic. It analyzes Delegated Proof of Stake (DPoS) as a form of programmed democracy, highlighting its tension between efficiency and fairness and its risk of oligarchic drift. The study contrasts algorithmic transparency with centralized control in Web2, framing blockchain as a new public square where trust flows through cryptography rather than ballots. Cryptocurrencies are interpreted as algorithmic artifacts—symbols of a democratized code economy—while cases like Dogecoin reveal how humor and creativity shape value systems in decentralized networks. Ultimately, the paper argues that blockchain governance requires not only technical precision but symbolic legitimacy, balancing innovation with ethical responsibility.

Jazmín María del Luján Gamarra Benitez

Ethereum block building has traditionally been approached using greedy algorithms that prioritize transactions with the highest fee per unit of gas. This work proposes an alternative that considers semantic interactions among transactions and operational constraints to define the utility of transaction combinations. Through a utility model that assigns bonuses and penalties to pairs and triples of transactions, we design algorithms capable of constructing blocks more valuable than those obtained by traditional methods. In experiments with 1,000 real transactions extracted from the network, two algorithms were implemented and evaluated, both grounded in a formulation inspired by job scheduling theory: a classic greedy baseline and the proposed heuristic. The base heuristic achieved approximately 86 % of the utility of the greedy approach ($6.78 \times 10^{20}$vs.$7.81 \times 10^{20}$) while including only 23 transactions. The extended version with greedy fill reached up to 120 % of the reference utility ($1.73 \times 10^{21}$), incorporating 268 transactions compared to 212 for the greedy, while maintaining execution times below 2 seconds. These preliminary results demonstrate the feasibility of capturing additional semantic value within time windows compatible with Ethereum block-building intervals, based on isolated experiments with bounded transaction sets.

Jamila Tileubaevna Arzieva, Ali Tileubaevich Arziev, Nawrızbay Baxtiyar ul Seytniyazov, Ilham Kongratbay ulı Tlemisov

THE ROLE OF ZERO-KNOWLEDGE PROOFS IN ENHANCING CRYPTOGRAPHIC PROTOCOLS // Universum: технические науки : электрон. научн. журн. Arzieva J.T. [и др.]. 2025. 10(139). URL: https://7universum.com/ru/tech/archive/item/21052

Dr. Muhammad Qasim Memon,Dr. Muhammad Naeem Akhter,Dr. Santosh Kumar Banbhrani,Zeeshan Qureshi

No abstract is available for this record.

Keke Gai, Chennan Guo, Jing Yu, Qiang Xiao · 6 authors

Distributed Ledger Technology (DLT) has emerged as a promising solution for constructing decentralized and trustworthy platforms in recent years. Although blockchain, as a form of distributed ledger technology known for its tamper resistance and trustworthiness, seems to be an ideal solution for addressing trust issues, common blockchain systems face limitations due to the ever-growing volume of data. In this paper, we propose a dynamic storage scheme calledEfficiency-awareLow-storageScalability (ELS), which allocates variable data storage for the distributed ledgers. Our approach is designed to provide load balancing and security, allowing dynamic nodes to join or exit the network seamlessly. We utilize graph theory to group storage nodes in the blockchain by determining their network distances. These groups are then mapped into points in a two-dimensional virtual plane, meaning that block storage depends on the coordinates within the virtual plane. To balance storage performance with the evolving block allocation strategy, we develop a Voronoi diagram-based method to achieve near real-time adoptions that meet dynamic allocation requirements in blockchain systems. Experimental evaluations have demonstrated that our approach can reduce storage requirements by approximately 93% at each node, compared to full replication in 10000 block chains.

Mehdi Nourinezhad, Yazdan Rezaei, Zeinab Kebriaei

Blockchain technology has emerged as a transformative force across various industries, including the energy sector. Energy Service Companies (ESCOs) play a crucial role in promoting energy efficiency and sustainability. This paper explores the potential impact of blockchain technology on ESCOs, focusing on how decentralized finance (DeFi) and blockchain can enhance operational efficiency, transparency, and trust in energy transactions. By leveraging blockchain, ESCOs can streamline energy audits, improve contract management, and facilitate peer-to-peer energy trading. This paper also discusses the challenges and opportunities associated with the adoption of blockchain technology in the ESCO sector, providing a comprehensive analysis of its potential to revolutionize energy services.

Denis Wapukha Walumbe, Gabriel Ndugu Kamau, Jane Wanjiru Njuki

Proof of Stake (PoS) models are energy-efficient and require limited computational power. These features are critical in telemedicine environments, where resource-constrained devices must handle sensitive data securely. The growing need for auditable and privacy-preserving data storage in telemedicine underscores the importance of PoS models optimized for lightweight devices while complying with strict regulatory requirements, such as the Health Insurance Portability and Accountability Act (HIPAA).This study was guided by two research questions: (i) Which PoS models are lightweight and suitable for telemedicine? and (ii) What features make lightweight PoS models effective for privacy and efficiency in telemedicine? To address these questions, a systematic literature review (SLR) guided by the PICOC framework was conducted to investigate lightweight PoS models that can enhance privacy in telemedicine systems. Out of 2,394 papers studies screened, 55 were included in the analysis. The findings identified Algorand, Ouroboros Praos, Tendermint, Nxt, and Casper CBC as promising candidates. Key enabling features included lightweight voting mechanisms, such as Byzantine Agreement protocols and Verifiable Random Functions, as well as cryptographic techniques like symmetric encryption and multiparty computation. Performance metrics evaluated included latency, throughput, energy efficiency, and battery consumption, with Grey Relational Analysis ranking Algorand highest due to its low latency, high throughput, and minimal energy consumption.