Blockchain Papers

Mathew Jyyothis Jimmy, Naveen John, V. Sreenath, Blerta Prevalla Etemi · 5 authors

No abstract is available for this record.

Igor, Chechelnitsky

This publication introduces Zero-Knowledge Behavioral Proof (ZKBP) as a post-biometric authentication primitive designed for the QADMON canonical security framework. ZKBP replaces traditional biometric and password-based identity with cryptographically verifiable behavioral continuity. The protocol proves liveness, integrity and continuity of behavior without revealing biometric templates, raw behavioral signals, or any permanent human identifier. The package includes: - Formal cryptographic definition of ZKBP - Security proofs under LWE-based post-quantum assumptions - Comprehensive threat model (AI imitation, replay, side-channels, insider threats) - Protocol specification in JSON - Comparative security tables (CSV) - Multilingual human-readable documentation (EN, RU, HE, ZH, AR) - Implementation notes for PQC + TEE environments This module follows the canonical QADMON axiom: FSIG ≠ Cryptographic Key FSIG = Zero-Knowledge Behavioral Proof The only cryptographic secret is a post-quantum key stored inside a Trusted Execution Environment (TEE). This work is published as Module 02 of the QADMON Canonical Security Framework.

akshitha

In the rapidly evolving landscape of cryptocurrency in India, a powerful new contender has emerged—Jaimax Coin, often hailed as the best presale crypto coin in India. As blockchain technology reshapes finance, digital ownership, and decentralized ecosystems, we stand at the forefront of innovation, introducing Jaimax, the next-generation crypto pre-sale coin designed for long-term scalability, high utility, and mass adoption. As a revolutionary new crypto coin India trusts for transparent and secure financial growth, Jaimax is strategically engineered to transform both the DeFi (Decentralized Finance) and NFT (Non-Fungible Token) markets. With advanced tokenomics, unmatched security standards, and a visionary roadmap, Jaimax is positioned to become one of the most influential digital assets in India’s expanding blockchain environment.

Yiming Zhao, Christopher Hayes

The complexity of modern supply chain networks requires sophisticated approaches to inventory management that can effectively handle demand uncertainty and coordinate decisions across multiple organizational levels. This paper proposes a novel hierarchical multi-agent reinforcement learning framework for dynamic inventory allocation in multi-echelon supply chains facing stochastic demand patterns. The hierarchical architecture decomposes the inventory control problem into strategic and operational decision layers, where high-level agents coordinate allocation policies across distribution networks while low-level agents optimize local replenishment decisions. The framework integrates Centralized Training with Decentralized Execution paradigm, enabling autonomous agents to learn coordinated policies through shared experience while maintaining operational independence during deployment. Experimental results demonstrate that the proposed approach achieves significant reductions in total system costs compared to traditional base-stock policies and single-agent reinforcement learning methods, while effectively mitigating the bullwhip effect in supply chains with high demand variability.

Remigio Santiago Siguencia Montero, Miriam Carmita Mora Urdiales

With the significant advancement of technology and networks at the global level, it can currently be observed that there is a wide digital access gap between urban and rural areas, a situation that creates a major obstacle to guaranteeing the right to education, especially for children and adolescents who live in areas where there are no internet connectivity towers and who, in addition, face extreme poverty that prevents them from acquiring an electronic device for their academic activities. Various statistical data on connectivity in rural areas identify the main factors that perpetuate inequality in access: infrastructure, affordability, and digital skills, situations that affect educational equity. According to evidence from studies carried out by international and regional organizations, several aspects that generate this problem are discussed, such as regulatory implications and, mainly, the poor implementation of public policies by the Central Government and the Autonomous Decentralized Governments. Based on this, recommendations are proposed for state institutions and multilateral actors aimed at ensuring meaningful connectivity and, in this way, guaranteeing the right to education in rural areas.

Sijie Cheng, Yanbo Yang, Jiawei Zhang, Pengfei Li

As fraud patterns in the Ethereum ecosystem become increasingly sophisticated, traditional detection methods face limited generalization capability and insufficient interpretability. Although Large Language Models (LLMs) possess powerful semantic understanding and reasoning abilities, their direct application in fraud detection still suffers from critical issues, including inadequate domain knowledge integration and scarcity of high-quality interpretable training data. To address these challenges, this paper proposes Large Language Model for Transaction Anomaly Detection (LLM-TAD), a framework that constructs interpretable training data through a dual interpretation strategy combining XGBoost with SHAP/LIME to provide complementary feature-level insights, and achieves domain knowledge injection and capability optimization via a two-stage approach involving supervised fine-tuning and instruction fine-tuning. Experimental results demonstrate that the proposed method achieves a fraud detection accuracy of 93.01% and an explanation quality (BERTScore) of 0.7939, achieving synergistic improvement in both accuracy and interpretability.

Tanya Zhelezniak, Ilan Alon

Abstract The metaverse is transforming many industries, customer behavior, and companies’ strategies. However, there is a lack of research and understanding of how to adjust existing approaches and solutions. Moreover, based on numerous studies, there is a strong connection between the metaverse and virtual technologies in general and non-fungible tokens (NFTs). The authors’ research aims to address this gap by investigating the reasons for this connection. The authors suggest that NFTs complement metaverse adoption and might be a key component for its business and marketing model developments. In addition, the authors provide specific guidance for NFT implementations in different industries. The authors’ contribution extends the knowledge of this nascent field and might be valuable for scholars and practitioners.

Shaolin Qiu, Shuchao Deng, Honglei Pang

No abstract is available for this record.

Tranquilli, Julius, Gupta, Naman

Concentrated-liquidity automated market makers (CLAMMs), as exemplified by Uniswap v3, are now a common primitive in decentralized finance frameworks. Their design combines continuous trading on constant-function curves with discrete tick boundaries at which liquidity positions change and rounding effects accumulate. While there is a body of economic and game-theoretic analysis of CLAMMs, there is negligible work that treats Uniswap v3 at the level of formal state machines amenable to model checking or theorem proving. In this paper we propose a formal modeling approach for Uniswap v3-style CLAMMs using (i) networks of priced timed automata (PTA), and (ii) finite-state transducers (FST) over discrete ticks. Positions are treated as stateful objects that transition only when the pool price crosses the ticks that bound their active range. We show how to encode the piecewise constant-product invariant, fee-growth variables, and tick-crossing rules in a PTA suitable for tools such as UPPAAL, and how to derive a tick-level FST abstraction for specification in TLA+. We define an explicit tick-wise invariant for a discretized, single-tick CLAMM model and prove that it is preserved up to a tight additive rounding bound under fee-free swaps. This provides a formal justification for the "$ε$-slack" used in invariance properties and shows how rounding enters as a controlled perturbation. We then instantiate these models in TLA+ and use TLC to exhaustively check the resulting invariants on structurally faithful instances, including a three-tick concentrated-liquidity configuration and a bounded no-rounding-only-arbitrage property in a bidirectional single-tick model. We discuss how these constructions lift to the tick-wise structure of Uniswap v3 via virtual reserves, and how the resulting properties can be phrased as PTA/TLA+ invariants about cross-tick behaviour and rounding safety.

Dr. Laila O. Karim

Rollups are central to blockchain scalability, but their governance is still evolving. Existing voting models risk capture by large stakeholders or inactive delegates. This paper introduces RepRoll, a governance model that uses delegated reputation scores backed by verifiable activity logs. Reputation grows through provable contributions: fraud-proof submissions, code audits, uptime guarantees, and community moderation. These contributions are recorded through a decentralized attestation layer similar to optimistic verification. Votes in protocol upgrades weigh both token stake and reputation, reducing plutocratic influence. A simulation of 10,000 participants demonstrates that RepRoll improves proposal quality and reduces governance attacks. We deploy a prototype on an Ethereum Layer-2 testnet, showing low on-chain overhead. The paper discusses vulnerabilities such as collusion, reputation laundering, and sybil amplification, and proposes cryptographic mitigations.

Rima Grati, Khouloud Boukadi, Safa Elleuch

The Proof of Stake (PoS) consensus mechanism is increasingly used in blockchain systems; however, resource allocation for PoS-based mobile blockchain networks remains underexplored, particularly given the constraints of mobile devices. This work introduces MEC-Chain, a new framework that integrates Mobile Edge Computing (MEC) with mobile blockchain to support efficient validator-node execution under PoS. MEC-Chain formalizes a multi-objective resource-allocation problem that jointly considers latency, reliability, and cost from both the validator and MEC-provider perspectives. To address this challenge, we develop a deep reinforcement learning-based allocation agent using the Proximal Policy Optimization (PPO) algorithm. Experimental results show that PPO achieves a 30–40% reduction in total execution time, 25–35% lower transmission latency, and 10–15% higher reliability compared to A2C (Advantage Actor–Critic) and DQN (Deep Q-Network), while offering comparable cost savings across all methods. These results demonstrate the effectiveness of MEC-Chain in enabling low-latency, reliable, and resource-efficient PoS validation within mobile blockchain environments.

Surendra Kumar Shukla, Vishan Kumar Gupta, Garima Sharma, Paras Jain · 6 authors

The applications of blockchain technology in a broad variety of contexts have become the basis of decentralized systems, and it has since grown much beyond its initial application to cryptocurrencies. This paper sheds light on two important bodies of research and provides an in-depth analysis of blockchain consensus algorithms. The former is the algorithm of Du et al. (2020) known as Mixed Byzantine Fault Tolerance (MBFT). Such MBFT illustrates a new solution to the fault tolerance and scalability problems of blockchain models of Ethereum and Bitcoin. Second, Chaudhry and Yousaf (2018) provided a clear analysis of consensus mechanisms. They went as far as to draw a comparative analysis of consensus algorithms, including but not limited to Byzantine Fault Tolerance (BFT), Proof of Work (PoW), and Proof of Stake (PoS). After conducting an extensive review and experimentation of each of the algorithms, relevant strengths, limitations, and suggestions on how to improve each of the analyses were brought to light in this paper. To summarize, the analysis given gives a platform to understand the area of future blockchain consensus research in security mechanisms, scaling solutions, and performance enhancement methods.

Shalu Mishra, Rajendra Kumar Dwivedi

No abstract is available for this record.

Tuan-Dung Tran, Quang Hieu Vu, Bao Huynh, Van-Hau Pham

No abstract is available for this record.

Alaa Tolah

The exponential growth of sophisticated cyber threats in Internet of Things (IoT) environments has exposed fundamental weaknesses in existing Cyber Threat Intelligence (CTI) platforms, including centralized architectures, trust deficits, privacy vulnerabilities, and single points of failure. To overcome these limitations, this paper proposes BlockIntelChain, a blockchain-based framework for secure, scalable, and collaborative CTI sharing across distributed IoT networks. The system integrates a hybrid consensus mechanism that combines Proof-of-Stake with reputation-based validator selection, supported by a multi-layered privacy framework employing Differential Privacy (DP), Zero-Knowledge Proofs (ZKP), Homomorphic Encryption, and Secure Multi-Party Computation. BlockIntelChain further embeds Federated Learning (FL) to enable distributed model training directly on IoT edge nodes without exposing raw threat telemetry. Comprehensive evaluations on real-world Malware Information Sharing Platform (MISP) datasets show that BlockIntelChain achieves 923 Transactions per Second at 500 nodes with 99.6% consensus success, while maintaining resilience against 51% and Byzantine attacks tolerating up to 33% malicious validators. Privacy analysis confirms an optimized utility-privacy trade-off, with DP (ε = 0.1) preserving 92% data utility and ZKP achieving 94% verification accuracy. The FL-based models outperform centralized baselines, reaching 96.4% accuracy for IoT malware classification, 94.7% for phishing detection, and 95.2% for network anomaly identification. Economic modeling validates sustainability through contributor growth (156 → 1,245 in 12 months) and improved contribution quality (0.73 → 0.92). The proposed framework directly benefits Security Operation Centers and edge-deployed IoT systems by enabling real-time threat intelligence exchange with strong security, privacy, and efficiency. Comparative benchmarking demonstrates BlockIntelChain's superiority over MISP, ThreatConnect, and IBM X-Force in decentralization, privacy, and cost efficiency, positioning it as a transformative solution for next-generation privacy-aware CTI ecosystems.

Richard Wiputra, Davis Kelvin, Theo Justin Amantha, Sonya Nadira Gularso

This paper introduces FOMOCheck, an artificial intelligence (AI) agent designed for the early detection of pump-and-dump (P&D) activities in the Solana blockchain ecosystem. The agent integrates CoinGecko market indicators with on-chain token-control features obtained via the Solana API to generate interpretable risk scores and explanations. In a backtesting evaluation involving 30 tokens identified as P&D schemes, FOMOCheck utilized only pre-dump information, achieving a recall of 70.0% and an F1-score of 82.4 % at a risk threshold of 6/10 or higher. A pilot deployment on 20 new token listings demonstrated end-to-end response times under 4.2 seconds (95th percentile), validating its feasibility for real-time triage and monitoring. A qualitative assessment revealed that the system generated transparent, metric-referenced explanations, although it demonstrated sensitivity to “green-flag” cues, such as price-volume alignment. The primary limitations include incomplete data on holder distribution and liquidity locks, as well as the lack of a balanced evaluation set containing non-P&D tokens. Future work will focus on expanding the dataset to include legitimate tokens, integrating streaming data connectors, and deploying a production-ready anomaly scoring API.

Kelly Vero

This chapter explores interoperability as the foundation for functional, inclusive and emotionally resonant digital experiences – from smart homes to the metaverse. Through critiques of Internet of Things (IoT), Non-Fungible Tokens (NFTs) and Web3, it argues for human-centred design that prioritises discoverability, dignity and decentralised control. Drawing lessons from games like Bury Me My Love and platforms like Spatial , it shows how autonomy, mastery and purpose (AMP) can guide persistent virtual worlds. Interoperability is reframed not just as a technical goal, but also as a social, economic and ethical imperative – crucial to everything from refugee support to metaverse monetisation.

Kelly Vero

This chapter traces the evolution of video game tech stacks from early home computing to modern metaverse platforms. Blending personal narrative with technical insight, it explores programming languages, modular design and infrastructure across MMOs, and Web2 and Web3 ecosystems. Games like Mined-Out , RuneScape , Jetpac and Tomb Raider illustrate how early innovation laid the groundwork for today&s;s persistent digital experiences. The chapter argues that game developers, with their systems thinking and user-centred design, are natural architects of the metaverse.

Kun Yang, Haihan Duan, Yu Zhao, Jian-Bo Cheng · 6 authors

With the rapid evolution of the Decentralized Web (DWeb), decentralized technologies have paved new avenues for Web3 applications and the authentication of digital assets. Among them, Non-Fungible Tokens (NFTs) have gained significant popularity due to their immutability and uniqueness, reshaping the landscape of artistic creation, marketing, and intellectual property protection. However, current blockchain-based NFT implementations still face core challenges within decentralized architecture: how to maintain decentralization while ensuring the visual uniqueness of digital assets and reducing storage costs. The rampant issue of duplication undermines the scarcity of digital art and erodes market confidence in copyright authenticity. Moreover, high gas fees and energy consumption further hinder the widespread adoption of NFTs, while reliance on external storage solutions like InterPlanetary File System (IPFS) introduces risks of data instability and loss. To address these challenges, this article presents the UniqueNFT framework, a novel architecture that deeply integrates blockchain oracles with decentralized storage verification mechanisms. The framework achieves three key technological breakthroughs: Using image inversion and generation techniques based on Encoder for Editing (E4E) and StyleGAN3, it extracts compact and expressive semantic features from NFT images, enabling efficient data compression and significantly reducing on-chain storage volume; The Crypto-Mask algorithm, by utilizing the hash value of blockchain user information (user-controlled SHA-256 digest of Ethereum address, user nickname, and registration time), ensures the visual uniqueness of NFTs; A smart contract extension compatible with the ERC721 standard, demonstrating UniqueNFT’s seamless integration within the blockchain ecosystem. By leveraging the technologies of the Decentralized Web, our framework represents an important step forward in enhancing the security and uniqueness of digital assets. It not only innovatively resolves the issues of NFT duplication and homogenization but also injects new vitality and long-term momentum into the creation of a trusted, sustainable blockchain-based digital asset ecosystem.

Ruidi Liu

This paper reviews the innovative applications of AI and Web3 in metaverse social platforms. It first analyzes the foundational roles of AI (e.g., virtual avatar generation, intelligent interaction, personalized recommendation) and Web3 (e.g., blockchain, NFTs, decentralized identity) in enabling immersive, secure, and user-centric social interactions. It then examines their synergies, with case studies of Decentraland and The Sandbox illustrating practical integrations. The research identifies key challenges, including technical bottlenecks (e.g., AI realism, blockchain scalability), user-related issues (e.g., awareness, privacy concerns), and industry-level hurdles (e.g., regulatory ambiguities, homogenization). Finally, it proposes future directions: advancing AI/Web3 technologies, expanding application scenarios across education and entertainment, and implementing strategic recommendations to foster inclusive and sustainable metaverse social ecosystems.

Davide Mancino

This paper analyzes the emerging memecoin phenomenon on the Solana blockchain, focusing on the Pump$.$fun platform during Q4 2024. Using on-chain data, it is explored how retail-focused token creation platforms are reshaping blockchain ecosystems and influencing market participation. This study finds that Pump$.$fun accounted for up to 71.1% of all tokens minted on Solana and contributed 40-67.4% of total DEX transactions. Despite this activity, fewer than 2% of tokens successfully transitioned to major decentralized exchanges, highlighting a highly speculative market structure. The platform experienced rapid growth, with daily active users rising from 60,000 to peaks of 260,000, underscoring strong retail adoption. This reflects a broader shift towards accessible, socially-driven market participation enabled by memecoins. However, while memecoins lower entry barriers and encourage retail engagement, they introduce significant risks. The volatile and speculative nature of these platforms raises concerns about long-term sustainability and the resilience of the blockchain ecosystem. These findings reveal the dual impact of memecoins: they democratize token creation and alter market dynamics but may jeopardize market efficiency and stability. This paper highlights the need to critically assess the implications of retail-driven speculative trading and its potential to disrupt emerging blockchain economies.

Enrique Lopez-Gonzalez

The contemporary academic ecosystem, heir to the Enlightenment's "Republic of Letters," finds itself in a state of profound and unsustainable crisis. That order, based on the free flow of correspondence and the disinterested pursuit of knowledge, has been supplanted by a system teetering under the weight of its own contradictions. This work embarks on a fundamental redesign to articulate an innovative and coherent framework for scientific communication. To this end, four distinct but complementary schools of thought are synthesized: From Ordoliberalism, we take the rigor of designing an "economic constitution" that prevents the concentration of power and fosters fair competition. From Humanistic Economics, we extract the telos, or normative purpose (human flourishing and shared prosperity). From Digital Humanism, we derive the technological ethos, ensuring that the infrastructure serves human dignity. Finally, from Decentralized Science (DeSci), we take the set of architectural tools (smart contracts, DAOs, tokens) capable of building this new order from the ground up. The narrative arc is deliberate: Part 1 offers an anatomy of decay, using the Uddin demand as a scalpel to dissect the economic, institutional, and epistemic pathologies of the current system. Part 2 articulates the philosophical constitution of the new republic. Part 3 details the architectural blueprint and technological infrastructure of this new order. Part 4 subjects this design to rigorous stress tests to forge its resilience and antifragility. Part 5 charts a strategic roadmap for the transition, a plausible path to navigate from the status quo to full community sovereignty. Finally, Part 6 brings the book full circle, returning to the foundational vision. This is a call to action to build the New Republic of Ideas that the pursuit of truth deserves in the 21st century.

Miranda Smith

High-containment laboratories (HCLs) are expanding worldwide as countries invest in infectious disease research and health security. These facilities are essential for developing vaccines, therapeutics and diagnostics, but their rapid growth has outpaced transparency and consistent oversight. Confidence in compliance with the 1972 Biological Weapons Convention (BWC) is weakened by these variations in regulatory capacity and reporting. Emerging technologies can help address these challenges. Artificial intelligence (AI) and distributed ledger technology (DLT) can strengthen national biosafety systems through enhanced data integrity, traceability and transparency in HCLs. Three use cases illustrate prospective applications: AI-enabled DNA screening to manage synthesis risks; safeguarding laboratory data and records with AI and DLT to improve accountability; and DLT-backed provenance tracking to monitor pathogen materials. Embedded within national oversight frameworks, these tools could enhance transparency and collaboration through more standardized reporting. In this way they could reinforce biological weapon prohibition norms and build confidence in peaceful intent.

Kolja Brockmann, Lauriane Héau

Emerging technologies risk charting new pathways for the development, production, acquisition and proliferation of biological weapons, but they also offer opportunities to help reduce these risks and to strengthen states’ implementation of their biological weapons non-proliferation obligations. For example, states are increasingly exploring the adoption of artificial intelligence (AI) and distributed ledger technology (DLT) to strengthen their implementation of export controls on dual-use items. National export control authorities are exploring possible applications of DLT to help verify strategic trade flows and the authenticity of associated documentation and the use of AI to help determine the classification of items. The Australia Group provides a possible forum for the export control authorities of its participating states to share experiences with such technologies. These could then feed into further discussions within the framework of the 1972 Biological Weapons Convention (BWC).