The exponential rise of blockchain technology is changing the way organizations operate, including in enforcement. Standard means of conflict resolution whether through courts or arbitration/mediation bodies, regularly face questions of cost, delay, jurisdiction and transparency. One of the innovations in an online and global market can be the blockchain-based decentralized judicial systems, as a result of such limitations. Family law disputes as a case study for the indepth analysis of DDR Blockchain-based Decentralized Dispute Resolution (DDR) systems, and how they could disrupt justice delivery processes in future. Both such models allow people to work out their differences without or so much help from a central authority. They accomplish this using decentralized governance, distributed ledgers, cryptographic security, and smart contracts. Disputes are settled using transparent rules, automated policing and community-based judgment. Critical topics are touched upon simultaneously: the legality of the system, pitfalls of bad governance, challenges to its scalability, voting biases in token systems and ethical dilemmas raised by machine decision-making. Decentralized methods of justice, the study suggests, are unlikely to replace courts as we know them in the near future. Rather, they're promising as secondary solutions - especially in the Web3 world, for digital assets, online commerce, and cross-border transactions. Blockchain dispute resolution can revolutionize the industry of justice in a digital era. It takes away intermediaries on the way to good legal systems through technology. This will enhance the legitimacy, effectiveness and accessibility of dispute resolution for all stakeholders.
In democratic systems, secure and transparent voting mechanisms are essential to maintain public trust and electoral integrity. Traditional paper-based and centralized electronic voting systems often face challenges such as limited transparency, risk of data manipulation, and dependence on centralized authorities. To address these issues, this project proposes a decentralized blockchain-based voting system designed to enhance security, transparency, and reliability. The system is developed on the Ethereum blockchain, where each vote is recorded as an immutable transaction to prevent tampering or duplication. Smart contracts written in Solidity automate essential election functions including voter registration, vote validation, and result computation. A web-based interface built using React.js and Web3.js enables secure interaction with the blockchain, while wallet-based authentication ensures that each authorized user can cast only one vote The system is implemented and tested in a controlled environment to evaluate performance, accuracy, and resistance to double voting.
Blockchain drives digital transformation in entrepreneurship by enhancing innovation, operational efficiency, and sustainable business practices. Alongside this development, big data analytics for sentiment insights plays an essential role in understanding public perception and consumer behavior, enabling strategic and data-driven decision-making. Blockchain's decentralized structure promotes transparency, security, and trust among stakeholders, supporting scalable and accountable business ecosystems. This study systematically reviews big data-driven sentiment analysis methods applied to blockchain-based entrepreneurial contexts such as ICOs, DeFi, and Web3 startups. It maps data sources, machine learning and deep learning architectures, and sentiment analysis tasks, explaining how sentiment insights contribute to investment evaluation, market prediction, and risk mitigation. Although blockchain offers significant benefits, its integration faces major challenges including ecosystem readiness, regulatory uncertainty, and limited workforce capability. This study highlights blockchain's role in improving competitiveness and sustainability, while identifying barriers and strategic responses needed to support innovation in digital entrepreneurship.
Although blockchain technology has demonstrated promise in various application fields, its technical intricacy, usability challenges and substantial onboarding obstacles impede broad mainstream acceptance. Earlier studies have primarily concentrated on protocol scalability, security and financial applications with less emphasis, on user adoption strategies. In response this paper aims to examine how these challenges are tackled and mass involvement is facilitated through gamified and mobile-centric Web3 ecosystems. The research conducts an evaluation of key Web3 platforms encompassing gamified tap-, to-earn frameworks, mobile-centric blockchain involvement approaches and social media-integrated mini-applications assessed through onboarding challenges, engagement strategies, network impact, token allocation and scalability metrics. The findings reveal that streamlined interaction designs, mobile compatibility and social connectivity have greatly lowered participation obstacles while maintaining user involvement and exponential expansion. Based on this, the paper therefore advances the GMS framework, which abstracts the adoption of blockchain as the additive influence of gamification, mobile-first design, and social-platform integration. The framework shifts the emphasis from infrastructure-centric optimization to user-centered system design and contributes to blockchain adoption research by providing insights relevant to the development of inclusive and scalable Web3 ecosystems.
The rapid growth of decentralized systems in theWeb3 ecosystem has introduced numerous challenges, particularly in ensuring data security, privacy, and scalability [3, 8]. These systems rely heavily on distributed architectures, requiring robust mechanisms to manage data and interactions among participants securely. One critical aspect of decentralized systems is key management, which is essential for encrypting files, securing database segments, and enabling private transactions. However, securely managing cryptographic keys in a distributed environment poses significant risks, especially when nodes in the network can be compromised [9]. This research proposes a decentralized database scheme specifically designed for secure and private key management. Our approach ensures that cryptographic keys are not stored explicitly at any location, preventing their discovery even if an attacker gains control of multiple nodes. Instead of traditional storage, keys are encoded and distributed using the BFLUT (Bloom Filter for Private Look-Up Tables) algorithm [7], which enables secure retrieval without direct exposure. The system leverages OrbitDB [4], IPFS [1], and IPNS [10] for decentralized data management, providing robust support for consistency, scalability, and simultaneous updates. By combining these technologies, our scheme enhances both security and privacy while maintaining high performance and reliability. Our findings demonstrate the system's capability to securely manage keys, prevent unauthorized access, and ensure privacy, making it a foundational solution for Web3 applications requiring decentralized security.
This paper introduces DMind-3, a sovereign Edge-Local-Cloud intelligence stack designed to secure irreversible financial execution in Web3 environments against adversarial risks and strict latency constraints. While existing cloud-centric assistants compromise privacy and fail under network congestion, and purely local solutions lack global ecosystem context, DMind-3 resolves these tensions by decomposing capability into three cooperating layers: a deterministic signing-time intent firewall at the edge, a private high-fidelity reasoning engine on user hardware, and a policy-governed global context synthesizer in the cloud. We propose policy-driven selective offloading to route computation based on privacy sensitivity and uncertainty, supported by two novel training objectives: Hierarchical Predictive Synthesis (HPS) for fusing time-varying macro signals, and Contrastive Chain-of-Correction Supervised Fine-Tuning (C$^3$-SFT) to enhance local verification reliability. Extensive evaluations demonstrate that DMind-3 achieves a 93.7% multi-turn success rate in protocol-constrained tasks and superior domain reasoning compared to general-purpose baselines, providing a scalable framework where safety is bound to the edge execution primitive while maintaining sovereignty over sensitive user intent.
Bikki Kumar, Dev Karan, Adarsh Kandu, Ashish Khari
The social impact of decentralised online communities, such as blockchain-based social networks, is complex because their decentralisation allows users to exercise greater freedom and independence. A novel Dynamic Graph Neural Network with Temporal Knowledge Distillation (DGNN-TKD) is proposed to model and predict influence patterns. DGNN-TKD differs from standard Graph Neural Networks (GNNs), which function under the assumption of static graphs. It tracks the temporal evolution of a graph, and introduces a knowledge distillation mechanism that enables the transfer of influence embeddings over time. We propose a novel multi-dimensional influence metric that captures agent reputation, engagement and trust, supplemented with robust attention-based temporal aggregation. In experiments on decentralized social network datasets, DGNN-TKD surpasses current dynamic GNNs in influence prediction, community detection, and misinformation detection in decentralized governance/Web3 applications. This framework connects graph-based learning and social dynamics and serves as a powerful tool to study decentralized phenomena.
We introduce FlashChain, a decentralized framework that integrates IO-aware attention mechanisms—especially FlashAttention—into scalable, trustless AI systems. As Transformer-based models become foundational to Web3 infrastructure (e.g., DAOs, decentralized search, autonomous agents), their quadratic compute and memory bottlenecks present critical challenges. FlashChain adapts block-sparse FlashAttention into a modular architecture optimized for multi-node, low-bandwidth environments typical of blockchain and edge networks. We propose a hybrid protocol combining attention kernel optimization with zero-knowledge verifiability, enabling real-time, trustless AI inference across distributed nodes. Benchmarks show 3–5× speedups and up to 30× gas savings per inference compared to baseline on-chain models.
The gig economy faces significant challenges with centralized platforms like Upwork and Fiverr, including high service fees (10–20%), opaque algorithms, unreliable reviews, and frequent payment disputes. To address these issues, this work proposes Work Bounty, a decentralized freelancing marketplace powered by Web3 and blockchain technologies. Built on the Ethereum blockchain, the platform utilizes smart contracts to automate critical processes such as job creation, bidding, work delivery, and escrow-based payments, thereby eliminating intermediaries and enhancing trust. Authentication is streamlined using MetaMask wallets, enabling secure, passwordless access tied to unique cryptographic addresses. Job details and deliverables are stored on the InterPlanetary File System (IPFS) to ensure immutable and tamper-resistant data storage, while a blockchain-based reputation system provides transparent, unalterable user ratings. Experimental evaluation on the Ethereum test network demonstrates that the system achieves a 100% success rate in smart contract executions and reduces overall transaction costs to 2–3% equivalent gas fees, compared to the 10–20% fees on centralized platforms. MetaMask authentication achieved a 98.7% success rate, and beta testing with freelancers and clients revealed 92% user satisfaction with the platform&s;s ease of use and trustworthiness. These results highlight the system&s;s potential to provide a secure, transparent, and cost-effective alternative to traditional freelancing platforms, fostering a more equitable and globally accessible gig economy aligned with Web3 principles.
This paper presents the implementation oriented development of an interactive web platform designed to bring transparency and trust to charitable giving through the use of blockchain technology. This DApp integrates both Web2 and Web3 components: Here organizations create verified charity campaigns so that donors contribute directly through Meta-Mask a cryptocurrency wallet, with all transactions immutably recorded on the blockchain for public auditability. The backend (Web2) manages user data, campaign verification, and document storage, enforcing legitimacy through decentralized storage (IPFS). Also with the use of web2 has helped to create a more user friendly and attractive user interface layouts. Etherium Smart contracts are used to handle and release donations based on predefined conditions. A Merkle Tree algorithm is implemented to provide cryptographic proof for inclusion of donations in charities. This platform solves common challenges of traditional charity systems, such as mismanagement, high intermediary fees, and mainly donor mistrust, by offering a secure, decentralized, and automated donation ecosystem.
NFTs, kurz für Non-Fungible Tokens, sind digitale Zertifikate auf einer Blockchain, einer unveränderlichen Datenbank. Sie zeigen, wem ein digitales Objekt gehört, beispielsweise eine Grafik, Audio-Dateien, In-Game-Items oder Tweets. Anders als klassische Dateien, die beliebig kopiert werden können, dienen NFTs als Eigentumsnachweis. Die eigentliche Datei liegt meist auf externen Servern. NFTs sind Teil der Vision des Web3, eines dezentralen Internets, in dem Nutzer*innen über Inhalte, Besitz und digitale Identitäten selbst bestimmen sollen. Das Konzept eröffnet neue Möglichkeiten in virtuellen Welten, Spielen und Community-Projekten, stößt aber an Grenzen, weil Plattformen, Wallets und Anbieter letztlich entscheiden, wer teilnehmen darf. Bekannt wurden NFTs ab 2020 im Kunst- und Sammlermarkt, beispielsweise Beeples Everydays oder Sammlungen wie CryptoPunks. In Games und virtuellen Welten wie Axie Infinity oder Decentraland lassen sich Besitzrechte, Handelsmechanismen und Community-Dynamiken praktisch nachvollziehen. Nach dem anfänglichen Boom sank ab 2023 der Wert vieler NFTs, Plattformen verschwanden und technische wie rechtliche Fragen blieben offen. Für die Medienpädagogik bieten NFTs zahlreiche Ansatzpunkte: Fachkräfte können mit Lernenden über digitale Besitzformen, Wertzuschreibung, Marktmechanismen und soziale Dynamiken diskutieren. Eigene Experimente – Tokens erstellen, Sammlungen aufbauen, Spielobjekte gestalten – machen Logik, FOMO-Effekte und Machtstrukturen erfahrbar. Gleichzeitig lassen sich Nachhaltigkeit, langfristige Verfügbarkeit von Daten und Zugangshürden kritisch reflektieren. NFTs bieten so einen Einstieg, um digitale Wertlogiken, Teilhabe und Verantwortung im Web3 zu hinterfragen.
Censorship resistance is a core value of Web3, yet practical access to decentralized websites remains dependent on centralized gateways such as ipfs.io, .link, and .limo, which are susceptible to regulatory takedowns and availability limitations. This paper investigates the technical barriers to truly censorship-resistant access in decentralized web architectures and presents an engineering-driven analysis of dweb3.wtf, a dedicated rendering gateway developed within the Web3Compass infrastructure. The system directly interfaces with decentralized name systems such as ENS and Unstoppable Domains, autonomously resolves content hashes via on-chain resolvers, and renders the associated IPFS-hosted sites via self-hosted infrastructure. By eliminating reliance on third-party APIs and centralized frontends, the gateway offers a robust alternative to Web2-style intermediaries. This paper presents the architecture, implementation, and performance characteristics of dweb3.wtf, evaluating its effectiveness in ensuring access continuity, domain coverage, and reduced external dependency.
It is an exploration of a decentralized social media platform, which uses blockchain and Web3 technologies to scale up privacy, security, and trust within users. The architecture uses Next.js as the front-end, solido as the smart contracts, IPFS as a distributed storage, and Web3.js to connect with the blockchain. It introduces canonical social-networking features, including user registration, content upload, like, comment and share. Notably, it keeps ownership of data to users, unlike the traditional centralized social-media platforms. The irreversibility of blockchain together with encryption makes sure that the content cannot be altered and the information about users is not at risk of unauthorized access. The system eliminates the possibility of exploiting the central level of control and increases the level of transparency. The performance appraisals indicate that the suggested platform provides better privacy, higher data security, and user agency than the mainstream networks. However, the issues of scalability and mass user adoption are still present, and the research should be further developed. This paper highlights how blockchain will reinvent social media, creating a just, transparent, and user-centric digital economy. Altogether, the study advances the discussion on decentralized social networks and demonstrates that blockchain can improve the level of trust and data protection in the process of online communication.
Xuehan Li, Tao Jing, F. Richard Yu, Hongwei Wang · 9 authors
Connected and autonomous vehicles (CAVs) enhance traffic efficiency and safety via massive data-driven computation and decision-making. The computational demands of massive data challenge centralized cloud networks, leading to a novel CAV paradigm supported by mobile edge computing (MEC) and built on Web3. CAVs in Web3 can efficiently and securely offload compute-intensive tasks to edge devices in a decentralized and self-controlled manner, necessitating dependable task offloading schemes. However, existing deep reinforcement learning (DRL)-based offloading schemes face two challenges: overlooking security risks like privacy exposure in dependability definitions, while being constrained by reward function formulation, resulting in poor generalization. In this paper, we propose a dependable offloading scheme based on intelligence and active inference for CAVs in Web3. First, we introduce a dependable offloading framework utilizing double-layer blockchain and decentralized identifiers to ensure offloading source dependability. Then, by introducing a security-measuring dependability metric called cost from energy consumption, delay, and privacy exposure risk (cEDP), we formulate the dependable offloading optimization problem from an intelligence and active inference perspective, enabling higher-level environmental cognition without rewards. The problem is solved by the proposed intelligence-based active inference (INAI) algorithm. Experimental results demonstrate that reward-free INAI outperforms mainstream DRL and heuristic approaches in convergence, efficiency, and generalization capabilities.
The InterPlanetary File System (IPFS) has been extensively promoted as a decentralized, censorship-resistant, and fault-tolerant storage protocol. This paper systematically dismantles these claims by demonstrating four critical and compounding vulnerability classes: (1) the structural dependency on centralized pinning services such as Pinata, Infura, and Web3.Storage, where compromising a single provider's dashboard or API effectively eliminates supposedly “immutable” content; (2) the futility of self-hosted pinning nodes as a mitigation strategy, given their susceptibility to targeted Distributed Denial-of-Service (DDoS) attacks capable of rendering them permanently unreachable; (3) the catastrophic implications of a cryptographic backdoor or collision discovery in SHA-256 or SHA-3 (Keccak), which would enable arbitrary content substitution while preserving valid Content Identifiers (CIDs), thereby destroying IPFS's fundamental integrity guarantees; and (4) the vulnerability of distributed pinning strategies to gossip-protocol-based reconnaissance attacks, wherein a state-level adversary (e.g., NSA, GCHQ, or equivalent) can enumerate all nodes hosting a target CID by compromising a single peer and leveraging protocol-level metadata propagation to systematically identify and neutralize every replica simultaneously. We formalize each attack vector with mathematical models, provide proof-of-concept algorithms, analyze the compounding effects of multi-vector attacks, and demonstrate that even the most sophisticated defense-in-depth strategies fail against a sufficiently resourced adversary. Our analysis conclusively establishes that IPFS, as deployed in practice, provides no meaningful censorship resistance and constitutes what we term Decentralization Theater—a system that employs the aesthetics and terminology of decentralization while maintaining the vulnerability profile of traditional centralized architectures, augmented by a dangerous false sense of security.
This research presents the design and implementation of the Decentralized Smart City of Things (DSCoT), a novel framework leveraging Web3 architecture to enhance the security and authentication of assets in cyber-physical systems (CPSs) for smart cities on a private blockchain. Unlike traditional non-fungible tokens that primarily identify and distinguish financial assets, existing approaches lack robust mechanisms for attributing and authenticating CPS assets such as owners, users, and IoT-enabled smart devices. DSCoT addresses this gap by introducing an extended ERC721 protocol, enabling IoT-enabled devices to have unique blockchain identities similar to user accounts, which enhances device management and tracking. Novel smart contract modules facilitate secure identification and authentication of CPS assets. Evaluated results on a private Hyperledger Besu blockchain show that DSCoT achieves significant performance improvements, including sub-second latency (∼0.1–0.5 s for application programming interface (API) calls), minimal transaction costs (∼0.01–0.05 USD), and a high processing capacity (∼1000 transactions per second (TPS)). These results, along with improved security through immutable authentication records, demonstrate DSCoT’s effectiveness as a scalable and secure solution for smart city CPSs.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Amid the institutionalization wave of Decentralized Finance (DeFi), U.S. institutional Liquidity Providers (LPs) have emerged as the core incremental capital for leading Decentralized Exchanges (DEXs). However, the adaptation gap between Uniswap V4's concentrated liquidity mechanism and institutional risk preferences, as well as regulatory compliance requirements, has hindered their market entry. This study focuses on the integration of "technical characteristics - institutional constraints - precise pricing" and constructs a machine learning pricing model optimized across three dimensions: return, risk, and compliance. By integrating Uniswap V4 on-chain data, institutional risk preference data, and market data, a Stacking ensemble architecture combining LightGBM and CNN-LSTM is designed, incorporating 22 core features to achieve precise pricing. Empirical results show that the model's Mean Absolute Error (MAE) on the test set was reduced by 37% compared to the benchmark, and the Root Mean Square Error (RMSE) is reduced by 42%. The Sharpe ratio reaches 1.87 (an increase of 62% compared to the benchmark), with a volatility of 15.3% and a compliance adaptability score of 91. In the case study, a $150 million liquidity supply achieved a 19.7% annualized return and an 8.3% maximum drawdown, successfully passing SEC compliance review. This research fills the gap in institution-oriented pricing models for V4, improves the institutional extension of Automated Market Maker (AMM) pricing theory, and provides a risk-controllable and compliance-adaptable pricing tool for U.S. institutions participating in DeFi, promoting the transformation of the DeFi ecosystem towards standardization and institutionalization. By aligning the V4 Hook mechanism with U.S. regulatory frameworks, this research provides a scalable technical standard for institutional DeFi adoption, reinforcing the competitive advantage of the U.S. Web3 financial ecosystem.
Multi-chain deployment has become a mainstream strategy for U.S.-based DAOs, yet treasury management faces three core bottlenecks: cross-chain liquidity fragmentation, inadequate compliance with U.S. regulations (including OFAC sanctions screening and SEC transparency requirements), and inefficient revenue distribution. Leveraging the incubation practices of over 12 U.S. DAOs (via daos.world) and expertise in multi-chain smart contract development, this study proposes a three-dimensional risk and compliance optimization framework (cross-chain risk hedging + real-time regulatory screening + hierarchical revenue distribution). Empirical testing on 8 U.S. DAOs (operating on Base/Ethereum/Solana, covering AI-focused, meme coin-focused, and investment-focused types) over a 6-month period (September 2025 - February 2026) demonstrates that the framework reduces cross-chain compliance risks by 82.3% (OFAC violation rate drops from 18.0% to 3.2%), increases the annualized treasury return rate by 17.6% (from 4.2% to 5.04%), lowers cross-chain transaction costs by 28.5% (average Gas fee decreases from $12.8 to $9.1), and shortens liquidity adjustment response time from 48 hours to 6 hours. Integrating U.S. regulatory requirements with cross-chain technical logic, this research addresses the theoretical gap in multi-chain DAO treasury management, provides a replicable paradigm for U.S. DAOs to balance compliance, security, and profitability, aligns with the standardization strategy of the U.S. Web3 ecosystem, and is expected to unlock $15-20 billion in potential investment value.
Jiaqi Gao, Zijian Zhang, Yuqiang Sun, Ye Liu · 8 authors
Business logic vulnerabilities have become one of the most damaging yet least understood classes of smart contract vulnerabilities. Unlike traditional bugs such as reentrancy or arithmetic errors, these vulnerabilities arise from missing or incorrectly enforced business invariants and are tightly coupled with protocol semantics. Existing static analysis techniques struggle to capture such high-level logic, while recent large language model based approaches often suffer from unstable outputs and low accuracy due to hallucination and limited verification. In this paper, we propose LogicScan, an automated contrastive auditing framework for detecting business logic vulnerabilities in smart contracts. The key insight behind LogicScan is that mature, widely deployed on-chain protocols implicitly encode well-tested and consensus-driven business invariants. LogicScan systematically mines these invariants from large-scale on-chain contracts and reuses them as reference constraints to audit target contracts. To achieve this, LogicScan introduces a Business Specification Language (BSL) to normalize diverse implementation patterns into structured, verifiable logic representations. It further combines noise-aware logic aggregation with contrastive auditing to identify missing or weakly enforced invariants while mitigating LLM-induced false positives. We evaluate LogicScan on three real-world datasets, including DeFiHacks, Web3Bugs, and a set of top-200 audited contracts. The results show that LogicScan achieves an F1 score of 85.2%, significantly outperforming state-of-the-art tools while maintaining a low false-positive rate on production-grade contracts. Additional experiments demonstrate that LogicScan maintains consistent performance across different LLMs and is cost-effective, and that its false-positive suppression mechanisms substantially improve robustness.
Abstract. The development of technologies for creating combat drones from civilian drones, the expansion of the practice of using these drones in ongoing military conflicts of varying intensity, as well as the development of artificial intelligence (AI) systems and the possibility of various combinations of AI with combat drones, constitute an already occurring, not yet fully understood, global security challenge that is dangerous for any existing country. The paper also examines the problem of an individual customer outsourcing the commission of an act of revenge or a terrorist attack to individual perpetrators, groups of perpetrators, as well as to AI systems that act autonomously using telecommunications networks, such as the Internet, robotics, and that conduct financing using cryptocurrencies. The security threats discussed here, in the context of the emergence of UAVs and other combat-purpose drones in private hands – supplied both from active armies and manufactured independently – represent a dual combination of threats to the established world order and opportunities for society. And it is clear that the security threat is not some ephemeral threat to the security of some ordinary voter, whose life and fate do not, in reality, interest anyone from the ruling stratum at all. The real security threat is the threat to the life, health, capital, and power of the stratum that rules society, as well as the risk that the service personnel of this stratum – in the form of intelligence services, security and judicial bodies, as well as the legislative branch – will be afraid to carry out the orders given to them, both those involving blatant violations of the law and those involving its simulated enforcement, aimed at continuing the exploitation of society under the guise of observing the constitution and other laws, conducting “a dog-and-pony version of democracy.” The other side of the coin manifests itself as “frontier justice” – the ability for an ordinary person to defend their violated rights even when the violator has an overwhelming advantage in the form of administrative, judicial, and financial resources. It should be taken into account that modern technologies – not only the combination of outsourcing with the use of public computer networks (Public Data Networks, PDN) to commit a crime, or the possibility of direct remote control of a drone, but also the possibility of using a drone with built-in AI deliberately trained to strike a target – are merely the tip of the iceberg that the “Titanic” of the established security system will collide with. Further technological development, in particular decentralized AI using Web 3.0 / Web3, will make it possible to use AI as the executor of a deceased person’s will, while transferring to the AI the necessary financial resources in cryptocurrency (including programming the AI to further criminal acquisition of funds for its activities), combined with the ability to use fab labs or to have the AI itself hire contractors, creates for the targets of an attack aimed by such an AI a situation of the inevitability of retribution. At the same time, these capabilities can be extrapolated to any life situations – for example, those involving deprivation of liberty, such as in connection with the abduction of any person following the example of the abduction of N. Maduro, or situations such as bankruptcy resulting from the bad-faith actions of counterparties. At the same time, the risk of retribution in the process of defending violated rights affects both rank-and-file executors – such as police officers and judges – and the real masters of the country in the form of the public and non-public elite. The latter situation – the threat to the lives of the elite – already appears to be a real problem requiring a solution. After all, it would be extremely painful for the ruling strata of countries that have fought wars and then reconciled – the main beneficiaries of the past war – to answer to the victims for crimes committed both during the war and during mobilization, even if the terms of peace provide for full amnesty. An absolutely unfamiliar sense of danger will also emerge among the ruling strata governing states that ignite wars and create crises, since they now find themselves in a vulnerable position. This situation is further aggravated by the fact that information – both factual and conspiracy theories – is now widely accessible and can serve as grounds for attacks on representatives of well-known families, both by informed individuals and by mentally ill people. Would the issue of depriving Denmark of Greenland even be on the agenda now if, during the 2024 assassination attempts on D. Trump (AP News, 2025; Reuters, 2025), terrorists had used not firearms but a group of fiber-optic drones with centralized AI trained to recognize its target? The third side of the coin will be the need to minimize offenses in society and to introduce mechanisms of genuine democracy and accountability of the authorities for the results of their activities, when the overwhelming majority of the population is involved in decision-making – from ensuring the functioning of a city district to the election of sheriffs, judges, prosecutors, and all the way to voting on draft laws as well as federal elections (see the experience of Switzerland). This system will make it possible to reduce the number of legal violations by representatives of the ruling strata and to hold them accountable for both past and ongoing crimes without the need for extrajudicial reprisals by private individuals. Concluding the enumeration of the main aspects of changes in public life caused by the development of private combat robotics, let us also consider the fourth side of the same coin. All the technologies and capabilities discussed can be implemented by a wide range of individuals with disturbed psyches, for example religious fanatics, as well as by criminal elements, for whom new technologies present the broadest opportunities for blackmail, robberies, and extortion. And it is precisely against such individuals that it will be necessary to create a security system of a new quality – one that does not yet exist – a security system costing hundreds of billions of euros for each country deploying it, ensuring comprehensive protection of society from new types of threats. Of course, it may seem that the development of such a security system is possible without social modernization of relations in society and without the introduction of mechanisms of real democracy. It may seem that the implementation of a police state based on a digital concentration camp is more preferable. Perhaps – but this would require conducting an experiment, for example following the model of Pakistan or the DPRK, where the ruling military or party elite lives isolated from the main part of the population. In doing so, the ruling stratum would have to survive under new conditions of total war with its own population, from whom, for the sake of “security,” absolutely all remaining freedoms would be taken away, following the example of the DPRK. The application of AI that can operate in our world after the death of the person for whom the AI serves as executor proves that the empirical rule “you can’t take your money with you” is gradually losing its meaning: AI or artificial consciousness (AC) makes it possible to practically and almost inevitably implement the will of either the deceased or, say, a person who has been imprisoned or kidnapped, as well as someone who has found themselves in other situations that limit their ability to act. In this regard, the next customer ordering the next kidnapping of N. Maduro will think very hard about whether it is worth dying from retaliatory actions by AI, or from the actions of an actor who has decided that the triggering event for the AI’s predefined action cycle has occurred. At the same time, an actor in the form of decentralized AI cannot be intimidated, bought, or destroyed. In effect, new technologies put at the disposal of private individuals and organizations what previously only states had at their disposal, in particular an analogue of a system like “Perimeter” (RVSN RF index 15E601, known in journalism as “Dead Hand”) (Stilwell, 2022). Of course, the AI (or AC) systems discussed above – first and foremost decentralized AI, designed so that they cannot be influenced or have their operating order changed either by shutdown or by blackmail involving the risk of shutdown – may also inherently carry socially constructive tasks. Already now, AI systems can function as independent and autonomous executors, even though they still contain certain built-in technological limitations. Even this, however, already makes it possible to use such systems effectively both as operational AI assistants and as systems for auditing human decisions for compliance with specified goals and/or means (Gudkov, 2020; Cowger, 2023; Li, 2024; Bell, 2025; Brennan, 2025; Brown, 2025). Here and throughout, wherever AI is discussed, the possibility of using an IS is also implied – one that differs from AI by the presence of a software equivalent of will. The rate at which AI systems operating in the PDN evolve into IS systems also operating in the PDN is not considered here, nor is the time it takes for laboratory IS systems to enter the PDN. And, as practice shows, innovations are primarily directed toward the sphere of committing crimes – for example, the elimination of undesirable individuals – an activity engaged in both by independent criminals, such as roaming bandits, and by the intelligence services and ministries of defense of stationary bandits – states. In this regard, although the fully robotic technologies discussed above, which do not involve human intervention in their operation from the moment of launch, can also be used for constructive activities, their priority emergence in cri
Open access
2 source records
Ethics and Social Impacts of AI
Legal, Health, Environmental and COVID-19 Challenges
The rapid global expansion of decentralized cryptoassets has confronted state authorities with complex regulatory, fiscal, and structural challenges.[1] In India, this tension is uniquely pronounced. The state has chosen to navigate private digital innovations by asserting its authority across multiple domains: maintaining structural barriers, implementing rigorous taxation frameworks, and advancing state-controlled alternatives. This research paper evaluates the three-dimensional matrix shaping India's cryptocurrency policy ecosystem: macro-legal uncertainty, systemic risks to financial stability, and the pursuit of digital sovereignty.By analyzing judicial shifts—such as the landmark Internet and Mobile Association of India (IAMAI) v. Reserve Bank of India case—alongside contemporary anti-money laundering amendments under the Prevention of Money Laundering Act (PMLA), the strict fiscal regimes established via the Finance Acts, and the parallel rollout of the Digital Rupee (e₹) as a Central Bank Digital Currency (CBDC), this paper demonstrates how India has constructed a de facto containment strategy. It concludes that while this approach has successfully mitigated systemic exposure and curbed capital flight, the persistent lack of an integrated statutory framework leaves retail investors exposed, keeps the domestic web3 ecosystem in legal limbo, and highlights the ongoing friction between private cryptographic protocols and sovereign monetary controls.
У статті досліджується Інтернет 3.0 як децентралізована, енергетично незалежна, штучно-інтелектуальна інфраструктура, що формується на перетині Web3, блокчейн-економіки, ядерної енергетики нового покоління та пост-сингулярних технологій. Аналізуються економічні, організаційні та правові аспекти переходу України до Інтернету 3.0 в умовах післявоєнної реконструкції та наближення до часу інтегрованої сингулярності. Особливу увагу приділено ризику «інтелектуального захоплення» – ситуації, коли технологічна сингулярність може привласнювати права людини на ідеї та інтелектуальний внесок. Автор обґрунтовує необхідність створення системи юридичної та фізичної фіксації і капіталізації прав людини на ідеї, висновки, розробки замість їх захоплення технологіями. Запропоновано концепцію «Інтернету свідомості» як децентралізованої мережі персоніфікованих цифрових двійників, де внесок кожної людини токенізується та захищається через блокчейн. Обґрунтовано, що поєднання енергетично та комунікаційно незалежних дата-центрів на базі малих модульних реакторів, національного блокчейну та Інтернету 3.0 надає Україні можливість стати частиною глобальної інфраструктури накопичення та примноження персоніфікованого інтелектуального капіталу.