The rapid evolution of cryptocurrency, blockchain technology, and Web3 ecosystems has significantly transformed global financial systems and digital economies. India has emerged as one of the largest cryptocurrency adoption markets due to increasing internet penetration, fintech innovation, digital payment infrastructure, and a young technology-oriented population. Simultaneously, the rise of decentralized finance (DeFi), tokenized assets, Central Bank Digital Currencies (CBDCs), and artificial intelligence integration with blockchain has redefined the scope of digital assets beyond speculative investment instruments. This research paper examines the emerging trends, regulatory developments, opportunities, and challenges associated with cryptocurrency and blockchain adoption in India in 2026. The paper also analyses government policies, taxation frameworks, investor behavior, cybersecurity risks, and institutional participation. The findings suggest that India possesses strong potential to become a global blockchain innovation hub if supported by balanced regulation, improved investor awareness, and sustainable technological development.
Non-fungible tokens (NFTs) have become a key asset class in Web3 markets, where visual artwork, textual narratives, and on-chain transaction patterns jointly determine value, yet their pricing dynamics remain volatile, opaque, and difficult to explain. Existing NFT valuation methods typically either ignore the multimodal nature of NFTs or treat assets as independent samples, failing to exploit the rich relational structures induced by shared creators, collections, and ownership patterns, and offering limited interpretability for high-stakes financial decisions. To address these challenges, we propose NFT-Insight, a multimodal graph transformer framework that unifies visual, textual, and blockchain information on a heterogeneous NFT graph and explicitly links structural and content signals to valuation behavior. The framework identifies closely related NFTs via a joint similarity measure in the multimodal embedding space, propagates information through a relation-specific graph attention network and a global transformer encoder, and adopts a regularization strategy that encourages consistent valuations for highly similar assets while still allowing data-driven differentiation. In addition, NFT-Insight integrates attention-based and SHAP-based explanations into a unified analysis pipeline, enabling joint study of valuation behavior and feature attributions at the level of related NFT pairs. Experiments on three large-scale, real-world NFT datasets show that NFT-Insight consistently outperforms strong unimodal, multimodal, and graph-based baselines, reducing MAE and RMSE by up to about 20% in static valuation (withR2up to 0.904), achieving robust cross-market performance with averageR2≈ 0.84 andr≈ 0.93, and attainingR2= 0.911 in temporal forecasting. Interpretability analysis reveals that visual, textual, blockchain, and graph-relational features achieve a high alignment between SHAP importance and attention weights (average Spearman correlation above 0.8), and case studies highlight meaningful valuation patterns driven by rarity, speculative trading, and temporal market shocks. Overall, the proposed framework offers a multimodal graph–based perspective on explainable NFT valuation and market forecasting, and provides a general template for incorporating complex relational and content interactions into graph-based learning in decentralized digital economies.
The Internet has evolved from its early promise of global connection and freedom into a centralized system dominated by Big Tech and governments, resulting in widespread data exploitation, surveillance, censorship, and erosion of user privacy and ownership. This paper traces the historical development of Web2 infrastructure, its foundational flaws—particularly the linkage of digital identities to real-world persons and the unchecked power of intermediaries—and the societal pressures that have exposed these vulnerabilities through events such as the Great Firewall of China, the Snowden revelations, the Cambridge Analytica scandal, and large-scale hacks. In response, the paper positions Web3 , underpinned by blockchain technology, as a necessary paradigm shift toward a decentralized, user-centric Internet. Web3 severs the tie between digital and physical identities, enables true data ownership, peer-to-peer encryption, global accessibility without geo-restrictions, and algorithmic governance that reduces reliance on potentially abusive middlemen. It argues that Web3 can encode core democratic values, including freedom of expression as articulated in Article 19 of the Universal Declaration of Human Rights, while addressing resistance from governments (concerned with control and taxation), Big Tech (threatened by loss of data monopolies), and everyday users (wary of complexity and perceived risks). The paper examines ethical considerations, potential misuse by bad actors, and the dual nature of technological innovation. It proposes four critical criteria for evaluating successful Web3 implementations: 1) affordability and equitable access with long-term cost reduction; 2) robust protection of individuals through privacy and bias mitigation, coupled with "freedom of speech, not reach"; 3) absence of any central governing body with control over development; and 4) a community-representative judicial system for handling violations of shared terms of service. Ultimately, this work contends that Web3 represents an inevitable evolution capable of empowering billions of users—particularly those in repressive regimes—by fostering transparency, equity, and self-governance, provided implementations adhere to these ethical and practical standards. It calls for cautious optimism, due diligence, and open-source verification in the transition to a more liberated and democratic digital era.
LIU Ronglong, LI Ziwei, WAN Yue, WU Jiajing, JIANG Zigui
As the paradigm of ″decentralized next-generation Internet,″ Web3, relying on blockchain technology, has become an emerging field with great potential in the digital intelligence service ecosystem. However, Web3 phishing websites pose a serious threat to ecological health. Phishers carefully design domain names as the primary bait, inducing users to visit and engage in high-risk operations to steal digital assets. Currently, the antiphishing works of Web3 primarily focus on phishing account detection, phishing transaction detection, and phishing gang mining, whereas the existing phishing website domain name detection primarily targets traditional phishing websites, which have limitations such as insufficient adaptability and a lack of systematic analysis. To this end, a detection method called WPWHunter is proposed for Web3 phishing website domain names, which conducts multidimensional analysis on the detected real Web3 phishing websites and explores the potential application of Large Language Model (LLM) in web page analysis. The WPWHunter algorithm detects three features in Web3 phishing website domain names: inducing words, visual deception, and item name imitation. The experimental results show that WPWHunter can effectively detect suspicious Web3 phishing domains with a G-means index of 0.769 on a test set, which is 0.048 higher than that of the best-performing baseline method. Additionally, as a supplementary exploratory experiment, three universal LLM are used to analyze the content of Web3 phishing websites that WPWHunter failed to detect and the logic used by LLM to determine Web3 phishing websites is summarized.
The rapid progress in quantum computing poses a severe risk to contemporary blockchain systems, as their reliance on vulnerable primitives like ECDSA and RSA allows quantum algorithms (e.g., Shor's) to break discrete logarithm and factorization problems, potentially enabling attackers to forge signatures, steal assets, impersonate users, and compromise ledger immutability—undermining the core trust model of decentralized finance and Web3 applications.To preempt this crisis, we propose a next-generation quantum-resistant multicchain blockchain architecture fused with an intelligent AI-powered Web3 threat firewall. The framework natively adopts NIST-approved post-quantum cryptography, integrating lattice-based ML-DSA (Dilithium) and hash-based SLH-DSA (SPHINCS+) schemes throughout the protocol stack: from secure key-pair generation in wallets, through transaction signing, to rigorous multi-node verification during consensus. This design ensures end-to-end protection against foreseeable quantum threats across diverse chains without requiring disruptive hard forks or retrofits.Comprehensive testnet experiments quantify the trade-offs: post-quantum signatures incur larger payload sizes (typically 2–4× compared to ECDSA) and modestly increased signing/verification times, yet the overall transaction processing capacity remains practical for everyday use, with throughput and latency suitable for high-volume decentralized applications. Storage and bandwidth overheads stay manageable through optimized encoding and pruning techniques.Augmenting cryptographic hardening, the AI threat firewall leverages machine learning models to perform real-time anomaly detection across multichain interactions, identifying subtle signature irregularities, suspicious patterns, and novel attack vectors—including those exploiting transitional quantum vulnerabilities—thereby providing adaptive, proactive defense beyond static primitives.These findings confirm that fully quantum-secure blockchain systems are deployable today with acceptable performance penalties, paving the way for resilient, future-proof Web3 infrastructure capable of withstanding the quantum era while preserving usability, scalability, and economic viability for global adoption.
ABSTRACT Blockchain technology has emerged as a foundational infrastructure for decentralized applications, where consensus protocols play a critical role in ensuring security, consistency and trust among distributed participants. This paper presents a comprehensive comparative analysis of nine widely adopted consensus protocols across public (proof of work [PoW], proof of stake [PoS], delegated proof of stake [DPoS]) and private (practical Byzantine fault tolerance [PBFT, Raft, Kafka, proof of elapsed time [PoET], yet another consensus [YAC], Paxos) blockchain systems. Unlike prior surveys, this work integrates workflow‐level operational modelling, quantitative performance comparison and application‐driven decision support within a unified analytical framework. Our analysis shows that PoW achieves strong decentralization at 3–15 transactions per second (TPS) with 10–60 min finality, whereas PoS improves throughput to tens to thousands of TPS with seconds‐to‐minutes finality while reducing energy consumption by approximately 99%. Private blockchain protocols such as PBFT and Kafka achieve sub‐second latency and throughput exceeding 10,000 TPS by trading off decentralization for performance and control. Furthermore, we develop a decision‐support framework that maps consensus mechanisms to application requirements and provides a critical synthesis of security risks, scalability limitations, and emerging solutions. The findings highlight that no single protocol satisfies all design goals, reinforcing the necessity of context‐aware consensus selection.
Abstract This article critically examines how Web3 decentralization policy trends impact global digital governance, questioning whether they genuinely distribute power or merely shift influence to a new, tech-savvy elite. Based on fieldwork in Silicon Valley since August 2022 and engagement with scholars and practitioners up to December 2025, the article provides a conceptual analysis with emerging empirical insights around the nascent global Web3 movement. While Web3 advocates challenge centralized data monopolies and traditional state structures, this analysis critiques the assumption that Web3 democratizes power, highlighting both its potential for inclusion and risks of exclusion, insofar as it may reinforce hierarchies rooted in technical expertise and digital access. While acknowledging the broader landscape of Web3 governance (including hybrid and federated models) and scoping the Global North and Global South contexts considering global adoption cases, the article particularly focuses on three post-Westphalian paradigms: (i) Network States, (ii) Network Sovereignties, and (iii) Algorithmic Nations. While Network States advocate for crypto-libertarian governance, Network Sovereignties and Algorithmic Nations emphasize cooperative governance aimed at empowering minority communities, such as indigenous groups, stateless nations, and e-diasporas, through decentralized, data-driven systems. By engaging with both the limitations and some promises, prospects, and pitfalls of Web3, this article questions whether Web3 can create a more inclusive global order or if influence is increasingly concentrated among a new elite. This article contributes to debates on sovereignty, governance, and citizenship by advocating hybrid policy frameworks that balance global and local dynamics, emphasizing solidarity, digital justice, and international cooperation for equitable Web3 governance.
Tato práce se zabývá integrací protokolu zkLogin do aplikace Web3, aby se uživatel mohl přihlásit pomocí účtu OpenID Connect místo správy seed phrase. Práce vysvětluje princip zkLogin, porovnává jej s jinými přístupy k autentizaci ve Web3 a implementuje prototyp pro Sui a Ethereum. Větev pro Sui používá nativní podporu zkLogin, zatímco větev pro Ethereum používá Groth16 důkaz, chytrý účet, registr JWK a ERC-4337. Jednoduchý lending scénář ověřuje opakované změny on-chain stavu po přihlášení. Výsledky ukazují, že zkLogin může zjednodušit onboarding a omezit přímé zveřejnění vazby mezi účtem Web2 a on-chain adresou, ale prototyp stále závisí na poskytovateli identity, salt service, proving infrastruktuře a správě veřejných klíčů.
Memory-enabled large language model (LLM) agents, particularly those deployed in long-horizon, tool-using settings such as Web3-style autonomous workflows, introduce security risks that extend beyond single-prompt injection. By persisting and reusing information across interaction steps and sessions, these agents enable memory poisoning attacks in which adversarial inputs modify persistent agent state and influence future decisions after benign intermediate interactions. Recent work on context manipulation and “fake memories” demonstrates that adversarial content can be injected into an agent’s prompt-visible inputs or persistent memory; however, existing evaluations largely analyze such attacks at isolated interaction steps or static context snapshots, obscuring their temporal dynamics. In this paper, we present the first large-scale, trajectory-level measurement framework for analyzing temporal memory poisoning in memory-enabled LLM agents. We construct a schema-constrained dataset of 2,614 multi-step attack trajectories spanning four attack families,chain poisoning, policy rewriting, backdoor triggering, andslow drift, executed over shared persistent memory. We define temporal risk metrics over multi-step interaction trajectories that capture delayed activation, non-monotonic escalation, and the earliest point at which attacks become distinguishable from benign behavior. Our empirical results show that a substantial fraction of attacks remain indistinguishable from benign behavior until late-stage activation, despite exhibiting low or medium risk at all earlier steps. Slow-drift and backdoor-trigger attacks, in particular, systematically evade step-local evaluation until terminal interactions, while chain poisoning and policy rewriting exhibit non-monotonic risk trajectories. These findings demonstrate that memory poisoning risk is inherently temporal and cannot be reliably assessed using prompt-level or step-isolated evaluation, motivating trajectory-aware benchmarks for agent security.
Financial markets often appear chaotic, yet ranges are rarely accidental. They emerge from structured interactions between market context and capital conditions. The four-hour timeframe provides a critical lens for observing this equilibrium zone where institutional positioning, leveraged exposure, and liquidity management converge. Funding mechanisms, especially in perpetual futures, act as disciplinary forces that regulate trader behavior, impose economic costs, and shape directional commitment. When funding aligns with the prevailing 4H context, price expansion becomes possible; when it diverges, compression and range-bound behavior dominate. Ranges therefore represent controlled balance rather than indecision, reflecting strategic positioning by informed participants. Understanding how 4H context and funding operate as market governors is essential for interpreting cryptocurrency price action as a rational, power-mediated process.
Khadija Sarwar, Syed Abid Ali Shah, Umar Ayaz Khan, Nosharwan Javied · 6 authors
Public and private sector tendering has traditionally relied on manual, paper-based, or loosely digitized workflows that are slow, opaque, and vulnerable to favouritism, record tampering, and unauthorized disclosure of bid information. Conventional e-tendering portals, although faster than paper-based processes, remain centralized, exposing them to a single point of failure and not guaranteeing that evaluation outcomes are auditable by bidders themselves. This paper presents the design and implementation of a Blockchain-Based Secure Tender Management System that uses Ethereum smart contracts, the Inter Planetary File System for decentralized document storage, and MetaMask-based identity/wallet management to automate tender publication, bid submission, evaluation, and contract award. The system is organized around two core smart contracts — a Listings Contract that manages tender creation, publication, and bidder communication, and an Agreement Producer Contract that manages award, billing, and payment logic — deployed and tested using Truffle and Ganache. By anchoring every transaction to an immutable, cryptographically verifiable ledger, the proposed framework removes intermediaries, enforces evaluation rules programmatically, and gives every stakeholder a synchronized, tamper-evident view of the tendering lifecycle. A review of blockchain-enabled procurement, construction-industry payment automation, and decentralized storage literature from 2020–2026 is used to contextualize the design choices and to identify open research directions, including scalability, gas-cost optimization, regulatory compliance, and integration with artificial intelligence for bid evaluation.
The proliferation of counterfeit products in various industries, including pharmaceuticals, electronics, and luxury goods, poses a significant threat to consumer safety, brand reputation, and economic integrity. Traditional verification methods often fail due to centralized control and limited traceability. This research proposes a block chain-based system to identify fake products by leveraging the decentralized, immutable, and transparent nature of block chain technology. The system records product information such as manufacturing details, origin, and ownership history on a distributed ledger, ensuring secure and tamper-proof tracking across the supply chain. Each product is tagged with a unique QR code that links to its block chain record, allowing end-users to verify authenticity through a mobile application. The system incorporates distinct login modules for administrators, sellers, and customers to ensure secure interactions and streamline product management. Simulation results validate the system’s capability to detect counterfeit products with high accuracy and real-time verification speed. The proposed solution provides a scalable and efficient framework for enhancing supply chain integrity and protecting consumers against fake goods
Blockchain technology has emerged as a revolutionary tool for securing online transactions by providing a decentralized, transparent, and immutable ledger for digital records. This technology operates on the principles of cryptography and consensus mechanisms, making it resistant to tampering and fraud. As online transactions have become an essential part of modern economies, ensuring the security and integrity of these transactions has become a critical challenge. Blockchain addresses these concerns by enabling peer-to-peer transactions without the need for intermediaries, thereby reducing the risk of fraud, data breaches, and financial theft. The purpose of this paper is to explore the role of blockchain technology in enhancing the security of online transactions, focusing on its implementation in various industries such as finance, healthcare, and e-commerce. This paper will analyze the fundamental features of blockchain, including its decentralized nature, transparency, and the cryptographic techniques used to ensure data integrity. Additionally, it will examine the challenges associated with the widespread adoption of blockchain, including scalability issues, regulatory concerns, and technological barriers. The paper also discusses the future potential of blockchain technology, particularly in relation to its integration with emerging technologies like artificial intelligence and the Internet of Things. By reviewing current trends, case studies, and research findings, this paper aims to provide a comprehensive analysis of blockchain technology’s impact on securing online transactions and its potential to revolutionize digital economies.
Indonesia’s fiscal decentralization provides village funds and tax revenue sharing funds to strengthen village autonomy, support public services, and enhance community economic welfare. This study examines the impact of village fund allocation, village fund, and tax revenue sharing funds on the economic welfare of communities across 13 villages in Murung District, Murung Raya Regency, from 2020 to 2024. Using a quantitative explanatory approach, the research applies descriptive and inferential statistical methods, including validity and reliability tests, multiple linear regression, and significance testing. The findings reveal that fund allocation, village fund, and tax revenue sharing funds significantly influence key indicators of economic welfare, such as household income, access to clean water, and the growth of active micro-enterprises. Among these, village funds emerge as the most dominant variable, contributing directly to economic participation and service access. The regression model demonstrates strong predictive power. These results align with theories of fiscal decentralization, public finance allocation, and welfare economics emphasizing the role of targeted fiscal transfers in reducing inequality and enhancing local development. The study recommends optimizing sharing funds for productive programs, integrating fiscal planning with SDGs and performance indicators, and strengthening governance, transparency, and community participation.
Persistent electricity shortages and routine load shedding have long hindered social and economic development in Pakistan, with Punjab its most populous and industrialized province bearing a disproportionate share of the burden. In recent years, however, solar power has emerged as a central pillar of provincial strategies to enhance energy security and reduce dependence on conventional, fossil-fuel-based generation. This paper examines how solar energy is contributing to Punjab’s gradual shift from chronic load shedding toward greater energy independence. Adopting a qualitative, multiple-case design, the study draws on national and provincial policy documents, secondary reports, and peer-reviewed literature. It focuses on four key sectors residential, agricultural, educational, and industrial where solar initiatives have been promoted through programs such as free solar panel schemes for low-income households, school solarization, solar irrigation systems, and industrial rooftop installations. A comparative sectoral analysis evaluates these initiatives in terms of affordability, reliability, sustainability, and scalability. The findings show that solar energy has significantly improved supply reliability for many households and institutions, reduced operating costs for some farmers and industries, and opened new avenues for decentralized generation. At the same time, coverage remains uneven, key programs are still small relative to overall need, and implementation is constrained by financing barriers, bureaucratic delays, and limited technical capacity. The paper argues that Punjab’s trajectory illustrates both the transformative potential and the persistent limitations of solar-led energy transitions in developing-country contexts. It concludes that scaling up equitable, decentralized solar adoption supported by robust provincial policies, innovative financing, and institutional reforms will be essential if solar power is to move from a complementary role to a structural driver of energy independence.