The Byzantine Generals Problem, introduced by Lamport, Shostak, and Pease, fundamentally addresses how a distributed system can achieve consensus even when some of its components are unreliable or malicious. This paper delves into the mathematical bounds that govern the solvability and efficiency of Byzantine Agreement (BA) protocols, specifically exploring the role of network topology in these limits. We examine classical impossibility results, such as the n $>$ 3f requirement for unauthenticated synchronous systems and the Fischer-Lynch-Paterson impossibility for deterministic asynchronous systems. Furthermore, we introduce "treasonous topologies" as a conceptual framework to systematically analyze how graph-theoretic properties like connectivity and diameter influence the minimum number of honest nodes required, message complexity, and time complexity. Special attention is paid to authenticated protocols which can relax certain bounds by employing digital signatures. This study elucidates the intricate relationship between adversarial capabilities, network structure, and the inherent mathematical constraints on achieving robust agreement in the presence of malicious nodes. We also touch upon modern applications in blockchain and distributed ledger technologies, where these theoretical bounds translate into practical considerations for security, scalability, and decentralization. A core contribution of this work is the synthesis of these established bounds with a detailed examination of how varying network structures fundamentally dictate protocol design and performance, offering a clearer lens through which to understand the vulnerabilities and strengths of real-world distributed systems.
As the world grapples with climate change and energy insecurity, renewable energy has emerged as a central pillar of sustainable development. However, the transition to renewables faces persistent technological, economic, policy, and social challenges. This paper explores the dual nature of renewable energy—its immense promise and its complex barriers—through global trends and India-focused case studies. By analyzing large-scale and decentralized renewable projects, including Bhadla, Pavagada, Rewa, and Kurnool solar parks, as well as microgrid initiatives in Dharnai and Indira Nagar, this study identifies strategic pathways for inclusive and resilient energy futures. The analysis reveals that integrated policies, innovative financing, community participation, and technological innovation are key to maximizing renewable energy’s transformative potential. Key words: climate change, energy, renewable.
Abstract Blockchain technology has become a transformative solution for secure and transparent digital ecosystems. This paper explores how decentralization, cryptographic hashing, distributed consensus, and immutable ledger architecture contribute to advanced data protection in the IT industry. The study integrates findings from existing literature, evaluates blockchain’s practical applications in sectors including finance, healthcare, supply chain, and governance, and examines a proposed multi-layer blockchain framework. The research highlights blockchain’s advantages in enhancing confidentiality, integrity, availability, and auditability, while identifying its limitations such as scalability, regulatory constraints, and environmental impact. Future scope emphasizes integration with AI, IoT, Web 3.0, quantum-resistant models, and cross-chain interoperability. Overall, the study concludes that blockchain is a critical technology for advancing trust-driven IT infrastructures. Keywords Blockchain, Data Security, Transparency, Decentralization, Smart Contracts, IT Industry
La investigación analiza la compatibilidad entre los contratos inteligentes basados en tecnología blockchain y el derecho al retracto reconocido en la legislación colombiana. Los contratos inteligentes permiten la ejecución automática de obligaciones mediante códigos informáticos almacenados en registros descentralizados, lo que garantiza seguridad, transparencia y eliminación de intermediarios. Sin embargo, una de sus principales características es la inmutabilidad de la información registrada, lo que dificulta la modificación, suspensión o reversión de los acuerdos una vez ejecutados. Esta situación genera tensiones con la naturaleza dinámica de las relaciones contractuales y con mecanismos jurídicos de protección al consumidor, como el derecho al retracto previsto en el Estatuto del Consumidor colombiano. Dicho derecho permite al consumidor desistir de ciertos contratos dentro de un plazo determinado, especialmente en modalidades de contratación donde no existe contacto directo con el producto o servicio. El estudio plantea que la rigidez inherente de la tecnología blockchain puede entrar en conflicto con principios fundamentales del derecho contractual, en particular con las facultades de modificación, terminación o arrepentimiento reconocidas por la ley. En consecuencia, se reflexiona sobre la necesidad de desarrollar contratos inteligentes que incorporen mecanismos jurídicos y tecnológicos capaces de armonizar la automatización de las obligaciones con la protección de los derechos de las partes y la flexibilidad requerida por las relaciones comerciales contemporáneas.
Hessah A. Alsalamah, Saeed Alqahtani, Ghazlan Al-Arifi, Jana Al-Sadhan · 8 authors
Assisted Reproductive Technology (ART), particularly In Vitro Fertilization (IVF), generates highly sensitive medical data classified as Protected Health Information (PHI) under international privacy and data protection laws. Ensuring the secure, transparent, and ethically governed management of this data is both essential and legally mandated. However, conventional Electronic Medical Record (EMR) systems often present significant challenges, including data-integrity risks, unauthorized access, and limited patient control—issues that become especially critical in contexts such as fertility preservation for cancer patients. EmbryoTrust introduces a blockchain-based framework designed to ensure the confidentiality, integrity, and availability of IVF-related information through a private, permissioned network integrated with role-based access control (RBAC). Smart contracts, implemented in Solidity on the Ethereum platform, verify spousal identities and enforce data immutability in compliance with religious legislation and ethical regulations. Off-chain data are stored in MongoDB for scalable, privacy-preserving management, while on-chain summaries provide tamper-evident traceability and verifiable auditability. The system was deployed and validated on the Ethereum Holešky testnet using Solidity 0.8.21 and Node.js 18.17, achieving an average transaction-confirmation time of 2.8 s, 99.9% uptime and a 95% user-satisfaction rate. Functional, integration, and usability testing confirmed secure and efficient data handling with minimal computational overhead. Comparative analysis demonstrated that the hybrid on-/off-chain architecture reduces latency and gas costs while maintaining automated compliance enforcement. The modular design enables adaptation to other jurisdictions by reconfiguring ethical and regulatory parameters within the smart-contract layer, ensuring flexibility for global deployment. Overall, the EmbryoTrust framework illustrates how blockchain logic can technically enforce medical and ethical rules in real time, providing a reproducible model for secure, culturally compliant, and privacy-preserving digital-health information management. Its alignment with Saudi Vision 2030 and the Wold Health Organization (WHO) Global Strategy on Digital Health 2020–2025 highlights its potential as a scalable solution for next-generation ART information systems.
Froylan Cortés-Santacruz, Luis Antonio Carrillo-Martínez, Luciano García‐Bañuelos, Jesús Anselmo Fortoul-Diaz
Although distributed ledger technologies (DLTs) have transformed financial sectors, their manufacturing applications lack systematic maturity assessment frameworks. Previous reviews identified DLT benefits but show critical gaps, including a lack of quantitative maturity metrics, insufficient categorization of use cases, and limited platform-specific comparative analysis. This systematic literature review addresses these gaps through three key contributions: (i) a novel Distributed Ledger Technology Maturity Level (DLTML) framework, (ii) a four-category manufacturing taxonomy, and (iii) platform-specific implementation analysis. Analyzing 60 primary studies (2018–2025) using Kitchenham’s guidelines, Wohlin’s snowballing, and Treiblmaier’s assessment framework, we answer the following: (i) What are the categories of use of DLT in manufacturing? (ii) What features of DLT are key enablers and what specific challenges have been addressed in current manufacturing solutions? (iii) What is the level of technological maturity of DLT applications in manufacturing according to the existing literature? The category Process Execution Tracking dominates (80 % of the studies), followed by Provenance (65 %), Ownership Management (30 %) and Payment Management (25 %). Smart contracts are the main enablers (81. 67 %), followed by decentralization (48.33 %). Governance mechanisms remain unaddressed, and interoperability progress is limited. Hyperledger Fabric leads privacy-sensitive scenarios (55 %), while Ethereum dominates transparency-focused applications (38 %). DLTML assessment shows that 61.66 % achieve intermediate maturity (DLTML-3), 20 % achieve high-fidelity prototypes (DLTML-4), but none achieves verified operational deployment (DLTML-5). This study provides evidence-based guidance for researchers and decision makers pursuing the adoption of DLT in manufacturing.
The paper explores the possibility of expanding the use of end-to-end encryption protocols based on the Double Ratchet algorithm in applications with low trust in the server, particularly in turn-based games and strategic interactions. The relevance of the research is due to the growing need for secure communication in cyberattacks, especially during military operations. The field of end-to-end encryption requires the study of additional applications beyond the usual ones, such as encrypted communication in text messengers. The developed implementation of the protocol can be safely used in any applications that aim to implement end-to-end encryption and satisfy the criterion of session ephemerality (in cases where secrets are stored outside a secure environment). The implemented server supports ephemeral sessions, which guarantee minimal risks of information compromise, and uses digital signatures (EdDSA) for user authentication. Logical routing of requests ensures efficient message transmission in secure scenarios. The choice of the classic game of checkers as an example allowed the authors to effectively demonstrate the advantages of end-to-end encryption and the capabilities of the implemented protocol. All cryptographic operations, including key generation, encryption and decryption of messages, are successfully performed on client devices. It is important to improve error handling mechanisms and optimize the operation of WebAssembly. An interesting area of further research is the creation of zero-knowledge proof mechanisms to prevent Man-In-The-Middle attacks during the creation of a shared secret, optimizing integration with cryptographic hardware security modules (HSM), and exploring the scalability of the solution. The proposed approach can be used to solve real-world information security problems where trust in the data transmission channel is critically important. Thus, the work has created a comprehensive solution that includes a cryptographic protocol, a backend, and a web client, which demonstrates the viability of end-to-end encryption in browser environments and multiplayer games. The work can be used as a basis for further research and development in the field of security of communication systems and privacy in multiplayer games.
Abstract We present a spatial analysis of Bitcoin-accepting merchants using BTC Map, a global crowdsourced dataset built on OpenStreetMap, to provide ground-level evidence on Bitcoin’s payment ecosystem. While prior research emphasizes macroeconomic drivers, our analysis of approximately 11,000 merchants shows that local adoption is more strongly shaped by community dynamics and sectoral niches. Acknowledging quality variance in crowdsourced data, we focus on verified regional clusters. We find a global concentration of adoption in the hospitality sector, localised clusters driven by grassroots initiatives rather than national policy and significant presence in alternative healthcare and IT services. These findings highlight the limits of top-down interventions such as El Salvador’s legal tender law and underscore the role of social networks in sustaining adoption. By contrasting spatial micro-level evidence with national studies, this work positions merchant data as a key lens for understanding Bitcoin’s evolving role as a medium of exchange.
Graph-structured data has become central to modern analytics, enabling institutions to model relationships in domains such as healthcare, finance, cyber security, and education. However, privacy regulations and institutional policies restrict the sharing of sensitive nodes, edges, or interaction logs, preventing the discovery of global graph patterns. This paper introduces a novel framework for Federated Graph Pattern Mining Across Institutions (FGPM-AI), enabling multiple organizations to collaboratively extract global sub graphs, motifs, and temporal patterns without sharing raw graph data. The framework proposes six novel contributions: (1) Privacy-Preserving Pattern Signatures (PPPS) for anonymized sub graph encoding, (2) Federated Temporal Graph Pattern Mining (FT-GPM) to learn evolving patterns across distributed graphs, (3) Zero-Exchange Federated Sub graph Matching (ZE-FSM) using zero-knowledge proofs, (4) Heterogeneity-Aware Graph Pattern Consensus (HGPC) for semantic alignment between distinct graph schemas, (5) Communication-Adaptive Pattern Sharing (CA-FGM) for bandwidth-efficient collaboration, and (6) Multi-Party Graph Pattern Distillation (MGPD) for merging patterns into a unified knowledge model. Experimental design considerations demonstrate the feasibility and robustness of the framework. The results highlight FGPM-AI as a promising direction for secure, scalable, and intelligent cross-institution graph analytics.
Byzantine Fault Tolerance (BFT) protocols are fundamental to achieving consensus in distributed systems where some nodes may behave maliciously. However, traditional BFT mechanisms often rely on strong trust assumptions in a majority of honest participants or incur significant communication overhead for extensive verification, thereby limiting scalability and introducing explicit points of trust. This paper proposes a novel approach to verifiable Byzantine agreement that leverages the power of Zero-Knowledge Proofs (ZKPs) to enhance trustlessness and verifiability. By integrating ZKPs into the consensus process, participants can cryptographically prove the correctness of their protocol actions and proposed states without revealing the underlying sensitive information or requiring every other node to re-execute complex computations. This paradigm shift enables a new class of BFT protocols where agreement is not merely reached but is {em verifiably} correct by any observer, reducing implicit trust and increasing transparency. We outline a conceptual framework for such a ZKP-enhanced BFT protocol, discussing the key integration points for zero-knowledge proofs, the expected benefits in terms of security and scalability, and the challenges associated with its implementation. Our approach aims to pave the way for more robust, scalable, and genuinely trustless decentralized systems.
Shrutika Singh, Anton Alyakin, Daniel Alexander Alber, Jaden Stryker · 12 authors
The performance of Large Language Models (LLMs) on multiple-choice question (MCQ) benchmarks is frequently cited as proof of their medical capabilities. We hypothesized that LLM performance on medical MCQs may in part be illusory and driven by factors beyond medical content knowledge and reasoning capabilities. To assess this, we created a novel benchmark of free-response questions with paired MCQs (FreeMedQA). Using this benchmark, we evaluated three state-of-the-art LLMs (GPT-4o, GPT-3.5, and LLama-3-70B-instruct) and found an average absolute deterioration of 39.43% in performance on free-response questions relative to multiple-choice (p = 1.3 * 10 -5 ) which was greater than the human performance decline of 22.29%. To isolate the role of the MCQ format on performance, we performed a masking study, iteratively masking out parts of the question stem. At 100% masking, the average LLM multiple-choice performance was 6.70% greater than random chance (p = 0.002) with one LLM (GPT-4o) obtaining an accuracy of 37.34%. Notably, for all LLMs the free-response performance was near zero. Our results highlight the shortcomings in medical MCQ benchmarks for overestimating the capabilities of LLMs in medicine, and, broadly, the potential for improving both human and machine assessments using LLM-evaluated free-response questions.
Open access
Artificial Intelligence in Healthcare and Education
Carl P. Lipo, Terry L. Hunt, Gina Pakarati, Thomas J. Pingel · 9 authors
Ethnohistoric and recent archaeological evidence suggest that Rapa Nui (Easter Island, Chile) was a politically decentralized society organized into small, relatively autonomous kin-based communities across the island. The more than 1,000 monumental statues (moai) of Rapa Nui thus raise a critical question: was production at Rano Raraku-the primary moai quarry-centrally controlled or did it mirror the decentralized pattern found elsewhere on the island? Using Structure-from-Motion (SfM) photogrammetry with over 11,000 UAV images, we created the first comprehensive three-dimensional model of the quarry to test these competing hypotheses. Our analysis reveals 30 distinct quarrying foci distributed across the crater, each containing redundant production features and employing varied carving techniques. This spatial organization, combined with evidence for multiple simultaneous workshops constrained by natural boundaries, indicates that moai production followed the same decentralized, clan-based pattern documented for other aspects of Rapa Nui society. These findings challenge assumptions that monumentality requires hierarchical control, instead supporting emerging frameworks that recognize how complex cooperative behaviors can emerge through horizontal social networks. The high-resolution 3D model also establishes a crucial baseline for the cultural heritage management of this UNESCO World Heritage site, while advancing methodological approaches for testing sociopolitical hypotheses through the spatial analysis of archaeological landscapes.
NFT (Non-Fungible Token) has emerged as a trending topic in the digital world. This article focuses on the working principle of NFTs and their practical applications in real-world scenarios. Ethereum blockchain serves as the foundational technology that powers NFTs. This document provides a comprehensive technical overview of Ethereum blockchain technology applied in the textile industry for maintaining product ownership verification and authenticity
Open access
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Legacy, profit-driven organizational structures often lack the adaptability, equity, and innovation required for the evolving complexities of contemporary patient-centered care. They can limit access, constrain options, impose financial burdens, and hinder optimized delivery. Here, we propose a new architecture for metaversal integrative healthcare using decentralized autonomous organizations (DAOs). Blockchain technology and smart contracts underpin equitable, transparent, and resilient health ecosystems beyond institutional gatekeeping and entrenched hierarchies. Central to this innovation is the introduction of Ecosystem Value Networks (EVNs), which quantify how diverse contributors, including patients, function as “wellness stewards” within decentralized, interconnected networks of value. EVNs represent a paradigm shift from transactional, top-down authority structures toward relational, emergent, and self-perpetuating interconnected systems. By programming prosocial principles into the architecture of DAOs via governance tokens, digitally encoded collective voting, autonomous smart contract enforcement, and transparency-by-design; these dynamics intrinsically reinforce collaborative over competitive behaviors and outcomes. Traditional institutions often reward dominance, prestige, and hierarchy, that represent conditioned patterns rooted in ancestral scarcity-based modes of fear and control; ill-suited for equitable healthcare. DAOs and EVNs, in contrast, condition new modes of operation grounded in abundance, interdependence, and shared stewardship. Over time, these digital frameworks can transform how health knowledge is generated, distributed, and enacted, establishing a “new normal” from the inside out, in which interconnectivity defines leadership and value. Moving from vision to strategy, this work maps a pathway toward truly participatory (opposed to nominal or symbolic), adaptive, and value-responsive healthcare systems for the new digital age.
Open access
Blockchain Technology Applications and Security
Legal, Health, Environmental and COVID-19 Challenges
<p>Existing financial systems are bloated with inefficiencies in their operation, lack of transparency and are characterized by and fallible and fragile accumulation points, whereas emerging decentralized finance (DeFi) platforms lack intelligent risk management, self-adaptive governance and provable security assurances. This paper proposes the Intelligent, Verifiable Financial Ledger (IVFL), a novel framework that harmoniously converts both Artificial Intelligence (AI) and blockchain to counteract their core drawbacks. AI-based smart contracts of a formally verifiable character that allows the intelligent, secure and auditable automated execution of complex financial transactions an agile and informed governance system, which is represented by the use of AI enhancements to the Decentralized Autonomous Organization (DAO). Simulation analysis shows that the IVFL framework enables substantial enhancements compared to baseline models, such as detecting anomalies with over 95% accuracy, decreasing operational overhead by 40 percent and becoming less vulnerable to coordinated network attacks. Coming back to provable security and adaptive intelligence, the IVFL framework represents a credible way of creating financial systems.</p>
Ke Zhang, Xiaoning Zhao, Chaocheng Zheng, Jiahong Ning · 8 authors
This study proposes Tool-RoCo, a novel benchmark for evaluating large language models (LLMs) in long-term multi-agent cooperation based on RoCo, a multi-robot cooperative benchmark. Recent research on LLM-based multi-agent systems has relied on predefined orchestration, while ignoring agent autonomy. Tool-RoCo treats other agents as tools and introduces cooperative tools, leveraging tool usage to evaluate multi-agent cooperation and self-organization. Tool usage means that each agent (LLM) selects a tool from a candidate set based on the current state, receives feedback, and adjusts its selection in subsequent rounds. To evaluate different autonomy levels, we propose four LLM paradigms: (1) centralized cooperation, where a single LLM allocates tools to all agents; (2) centralized self-organization, where a central LLM autonomously activates agents while keeping others inactive; (3) decentralized cooperation, where each agent has its own LLM and calls tools based on local information; and (4) self-organization, where a randomly chosen initial agent can request collaboration, activating additional agents via tool calls. Tool-RoCo includes three multi-robot tasks, SORT, PACK, and CABINET, to measure format and parameter accuracy and agent coordination through tool usage. The results using several LLMs showed that cooperative tools accounted for only 7.09% of all tools, indicating that LLM-based agents rarely invoked others as assistants. Moreover, activation tools accounted for 96.42%, suggesting that current LLMs tend to maintain active agents while seldom deactivating them for adaptive coordination. Tool-RoCo provides a systematic benchmark to evaluate LLM autonomy and cooperation in multi-agent tasks. Code and Demo: https://github.com/ColaZhang22/Tool-Roco
Distributed Ledger Technology (DLT) as a principle of corporate governance represents an institutional shift of the law of the firm. Once relegated to academic theorizing and cryptocurrency, DLT now forms institutional infrastructure with a nascent market of tokenized real-world assets (RWAs) surpassing $33B at the close of Q4 2025. This paper analyzes how DLT intersectors three pillars of management - Strategic, Operational and Financial - in conjunction with Transaction Cost Economics (TCE) and Agency Theory that also coincide with inextricably lower baseline costs of trust and coordination. Strategically, Decentralized Autonomous Organizations (DAOs) and Intellectual Property Non-Fungible Tokens (IP-NFTs) are increasingly at the forefront of governance and R&D-related compensation structure. Operationally, smart contracts govern supply chains at near-real time with the Global Shipping Business Network (GSBN) going live with container tracking implementations and the FDA implementing pilot programs for near-instant visibility into temperature-controlled shipping needs. Financially, treasuries and debt instruments are increasingly tokenized to allow firms to harness an illiquidity premium while equitizing their working capital. Ultimately, this research concludes that the international financial architecture is bifurcated as high-stable assets transition to permissioned DLTS while high-velocity assets remain in public programmable spaces.
There has been an exponential rise of Internet of Things (IoT) devices and autonomous systems, which have thrown light on the weaknesses of centralized cloud computing, especially in latency, bandwidth, and security. This paper will solve such problems by suggesting an integrated blockchain-edge architecture, which uses distributed trusting mechanisms to protect and optimize edge networks. The process of the methodology consists of four steps: architectural modeling, lightweight consensus design, performance-security trade-off analysis, and real-life validation. Experiments with iFogSim and BlockSim showed that edge networks enhanced with blockchain cuts latency and bandwidth consumption by 37 and 36 percent respectively compared to cloud-centric models. Consensus protocols such as Practical Byzantine Fault Tolerance (pBFT), Proof-of-Elaboration (PoE) and Leased Proof-of-Stake (LPoS) were designed and tested, using much less energy and having much faster transaction finality compared to Proof-of-Work. High resilience to Sybil, tampering, and 51% attacks was proven with Raspberry Pi clusters, and an 8% latency trade-off was observed, when smart contracts were used to enforce automated access control. Lastly, experimental validation with healthcare and industrial IoT datasets demonstrated that blockchain decreased attempts to access information unauthorized to nearly zero in the healthcare industry and minimized manipulations with machine logs by 70 percent in the industrial IoT. These results highlight blockchain-edge convergence as a potential direction towards the construction of scalable, secure and trustful decentralized systems.
The convergence of artificial intelligence (AI) and decentralized web technologies represents a pivotal shift in digital infrastructure, giving rise to the concept of AI-native protocols. These protocols integrate AI capabilities directly into their fundamental design, moving beyond mere application-level AI to create intelligent, adaptive, and autonomous decentralized systems. This paper explores the transformative potential of AI-native protocols in reshaping the decentralized web, often referred to as Web3. We delve into the architectural implications, key benefits such as enhanced security, efficiency, and scalability, and the profound societal impact of such a paradigm shift. Through a comprehensive literature review, we identify existing challenges in both AI and blockchain domains that AI-native protocols are uniquely positioned to address, including algorithmic bias, data privacy, and consensus mechanism inefficiencies. We propose a conceptual framework for designing these protocols, emphasizing core components like intelligent consensus, autonomous agents, and AI-powered smart contracts. Furthermore, the paper discusses the ethical considerations inherent in embedding AI within decentralized governance structures and outlines future research directions for fostering responsible innovation. Our findings suggest that AI-native protocols are not merely an incremental improvement but a foundational evolution that promises to unlock unprecedented levels of intelligence and autonomy across the decentralized digital landscape, fostering a more robust, equitable, and resilient internet.
Behavioral finance explores the psychological influences and cognitive biases that affect investor behavior and financial decision-making, including herding, the disposition effect, overconfidence, and others. Algorithmic trading is a method that uses computer programs to automatically execute buy and sell orders based on predefined mathematical models and trading strategies. With the continuous development of modern technology, the advent of the Web3 era, and the gradual evolution of artificial intelligence, algorithmic trading is becoming increasingly prevalent and garnering significant attention. While algorithmic trading is automated and may seem immune to human cognitive biases, the opposite is often true. This study aims to review the main findings of existing research from the perspective of the stock market, exploring the interactive relationship between behavioral finance and algorithmic trading and how cognitive biases such as herding and the disposition effect can influence algorithm performance. The results emphasize the importance of behavioral finance in both the research and practice of algorithmic trading, while also proposing the potential for using machine learning techniques to advance the field of behavioral finance. By integrating existing theories, this study contributes to a deeper understanding of the relationship between behavioral finance and algorithmic trading and offers new perspectives for its future development.
Matteo Bjornsson, Taylor Hardin, Taylor Heinecke, Marcin Furtak · 6 authors
Distributed ledger technologies (DLTs) rely on distributed consensus mechanisms to reach agreement over the order of transactions and to provide immutability and availability of transaction data. Distributed consensus suffers from performance limitations of network communication between participating nodes. BLOCKY ZipperChain guarantees immutability, agreement, and availability of transaction data, but without relying on distributed consensus. Instead, its construction process transfers trust from widely-used, third-party services onto ZipperChains's correctness guarantees. ZipperChain blocks are built by a pipeline of specialized services deployed on a small number of nodes connected by a fast data center network. As a result, ZipperChain transaction throughput approaches network line speeds and block finality is on the order of 500 ms. Finally, ZipperChain infrastructure creates blocks centrally and so does not need a native token to incentivize a community of verifiers.
Mohammad Alvian Dharma Nararya, Shuri Mariasih Gietty, Himawan Aditya Pratama
Tulisan ini mengkaji secara kritis kemunculan gim Play-to-Earn (P2E) dalam kerangka teknologi Web3, dengan berargumen bahwa janji desentralisasi yang dibawa oleh blockchain dan Non-Fungible Token (NFT) justru mereproduksi, bahkan memperkuat, pola-pola eksploitasi kapitalisme tradisional. Model P2E merujuk pada sistem permainan digital yang memungkinkan pemain memperoleh keuntungan finansial dari aktivitas bermain melalui mekanisme ekonomi berbasis token kripto, di mana aset dalam gim memiliki nilai tukar di pasar digital. Sementara itu, blockchain merupakan teknologi pencatatan terdistribusi yang menyimpan data transaksi di banyak komputer (nodes) dan sering diklaim sebagai fondasi desentralisasi digital karena tidak bergantung pada otoritas tunggal. Melalui analisis terhadap infrastruktur Web3 dan studi kasus gim Axie Infinity (2018), tulisan ini menunjukkan bahwa sistem digital yang diklaim membebaskan pengguna dari kontrol terpusat justru memusatkan kekuasaan ekonomi dalam bentuk yang lebih terselubung. Dengan kerangka teori kapitalisme digital dan konsep false needs dari Herbert Marcuse, penelitian ini memperlihatkan bahwa ekonomi P2E mengubah aktivitas bermain menjadi bentuk kerja (playbor) dan menundukkan pemain pada pasar spekulatif yang menguntungkan pengembang dan pemilik modal. Di Asia Tenggara, tempat basis pemain P2E tetap besar meskipun gelembung pasarnya telah pecah, sistem ini mengeksploitasi kondisi sosial-ekonomi yang rentan dengan membingkai ketidakstabilan finansial sebagai peluang. Tulisan ini berargumen bahwa “desentralisasi” dalam Web3 merupakan bentuk sentralisasi terselubung melalui kontrol algoritmik, opasitas infrastruktur, dan privatisasi platform, menunjukkan bahwa Web3 dan gim P2E bukanlah alternatif pasca-kapitalis, melainkan fase baru dari kapitalisme digital yang mengomodifikasi permainan dan mendistribusikan risiko ke bawah sambil mengonsolidasikan keuntungan di atas.
The Paris Journal on AI & Digital Ethics Bootstrapping Trust across Web2 and Web3 Domains Using Publicly Verifiable Web Data Yuan Lu¹, Qiang Tang² Corresponding authors:luyuan@iscas.ac.cn • qiang.tang@sydney.edu.au Abstract Through […]