This paper investigates whether Bittensor can be considered the Bitcoin of decentralized Artificial Intelligence by directly comparing its tokenomics, decentralization properties, consensus mechanism, and incentive structure against those of Bitcoin. Leveraging on-chain data from all 64 active Bittensor subnets, we first document considerable concentration in both stake and rewards. We further show that rewards are overwhelmingly driven by stake, highlighting a clear misalignment between quality and compensation. As a remedy, we put forward a series of two-pronged protocol-level interventions. For incentive realignment, our proposed solutions include performance-weighted emission split, composite scoring, and a trust-bonus multiplier. As for mitigating security vulnerability due to stake concentration, we propose and empirically validate stake cap at the 88th percentile, which elevates the median coalition size required for a 51-percent attack and remains robust across daily, weekly, and monthly snapshots.
The rapid growth of cryptocurrencies and digital assets has created significant challenges for governments in regulating economic and business activities. Both Indonesia and India face similar issues concerning legal certainty, investor protection, and financial stability, yet they have adopted different regulatory approaches. This research aims to analyze and compare the regulatory frameworks governing cryptocurrencies and digital assets in Indonesia and India, using a comparative legal method that examines legislation, regulatory guidelines, and policies in both countries, supported by doctrinal interpretation and secondary literature. The findings reveal that Indonesia officially prohibits the use of cryptocurrencies as a means of payment but allows them to be traded as commodities under the supervision of the Commodity Futures Trading Regulatory Agency (Bappebti). In contrast, India has demonstrated a dynamic regulatory stanceβinitially imposing restrictions on cryptocurrency activities, later introducing a taxation framework, and currently considering the implementation of a central bank digital currency (CBDC). Despite these differences, both jurisdictions share the same fundamental objectives: to safeguard the financial system, prevent money laundering, and protect consumers. Indonesiaβs approach emphasizes strict market controls and legal certainty through prohibitions on payment functions, while Indiaβs model reflects regulatory fluidity and growing fiscal integration. This comparative analysis underscores the evolving nature of cryptocurrency governance in developing economies and highlights the need for balanced frameworks that promote innovation while maintaining financial stability and legal coherence.
Cooperative multi-UAV clusters have been widely applied in complex mission scenarios due to their flexible task allocation and efficient real-time coordination capabilities. The Air Command Aircraft (ACA), as the core node within the UAV cluster, is responsible for coordinating and managing various tasks within the cluster. When the ACA undergoes fault recovery, a handover operation is required, during which the ACA must re-authenticate its identity with the UAV cluster and re-establish secure communication. However, traditional, centralized identity authentication and ACA handover mechanisms face security risks such as single points of failure and man-in-the-middle attacks. In highly dynamic network environments, single-chain blockchain architectures also suffer from throughput bottlenecks, leading to reduced handover efficiency and increased authentication latency. To address these challenges, this paper proposes a mathematically structured dual-chain framework that utilizes a distributed ledger to decouple the management of identity and authentication information. We formalize the ACA handover process using cryptographic primitives and accumulator functions and validate its security through BAN logic. Furthermore, we conduct quantitative analyses of key performance metrics, including time complexity and communication overhead. The experimental results demonstrate that the proposed approach ensures secure handover while significantly reducing computational burden. The framework also exhibits strong scalability, making it well-suited for large-scale UAV cluster networks.
This article discusses the comparison between the public sector and the private sector in terms of goals, financing, and organizational structure. The public sector focuses on public services and fulfilling basic needs, with limited resource management and a more complex bureaucracy. In contrast, the private sector prioritizes profit and efficiency, with a more flexible and decentralized organizational structure. Public sector financing is based on taxes and community contributions, while the private sector relies on investors, debt, and equity capital. While both sectors play complementary roles, this article also identifies the challenges each sector faces in resource and managerial management. Implications and recommendations for both sectors are discussed to enhance operational efficiency and sustainability.
With the globalization of the software industry, requirements traceability has become increasingly critical in the software development process. However, the development of large-scale, complex software systems by cross-organizational research teams often faces challenges due to diverse organizational backgrounds, multi-site environments, conflicting objectives, and organizational boundaries. These factors can lead to trust issues, complicating the implementation of requirements traceability. To address these challenges, this study proposes a Smart Contract-Based Requirements Traceability (SCRT) framework. Smart contracts, which are executable code deployed on a blockchain, exhibit properties such as enforceability, tamper resistance, and verifiability. These characteristics empower the SCRT framework to enhance collaboration, communication, and trust among stakeholders while potentially improving the efficiency and quality of software development. Within the SCRT framework, a novel Requirements Traceability Information Model (RTIM) is introduced, which categorizes the links between new and existing artifacts. This model serves as a guide for the smart contract module, delineating which software artifacts to trace and the relationships to establish.
Due to the scalability and portability, the low-altitude intelligent networks (LAINs) are essential in various fields such as surveillance and disaster rescue. However, in LAINs, unmanned aerial vehicles (UAVs) are characterized by the distributed topology and high dynamic mobility, and vulnerable to security threats, which may degrade the routing performance for data transmission. Hence, how to ensure the routing stability and security of LAINs is a challenge. In this paper, we focus on the routing process in LAINs with multiple UAV clusters and propose the blockchain-enabled zero-trust architecture to manage the joining and exiting of UAVs. Furthermore, we formulate the routing problem to minimize the end-to-end (E2E) delay, which is an integer linear programming and intractable to solve. Therefore, considering the distribution of LAINs, we reformulate the routing problem into a decentralized partially observable Markov decision process. With the proposed soft hierarchical experience replay buffer, the multi-agent double deep Q-network based adaptive routing algorithm is designed. Finally, simulations are conducted and numerical results show that the total E2E delay of the proposed mechanism decreases by 22.38\% than the benchmark on average.
This research aims to spread the implementation of blockchain technology in the digital financial sector through a literature study approach. The main issue raised is how blockchain is applied in financial services and what challenges and benefits come with it. The method used was a literature review of 18 relevant scientific articles. The analysis results show that blockchain has been implemented in four main categories, namely cryptocurrency, cross-border payments, decentralized finance (DeFi), and smart contracts. This implementation provides significant benefits such as transparency, cost and time efficiencies, and increased security. However, blockchain implementation still faces serious challenges such as regulatory ambiguity, scalability issues, cybersecurity risks, and low adoption by traditional financial institutions. This research suggests the importance of strengthening regulations, technical innovation, and increasing technological literacy to encourage broader and more effective blockchain implementation in digital financial systems.
Pollution attacks, such as transaction spam or fake data injection, undermine blockchain efficiency and security.This paper proposes a smart contract-based framework to autonomously detect and mitigate such attacks in real time.By embedding heuristic rules and anomaly detection logic into smart contracts, our system identifies malicious activity (e.g., excessive invalid transactions) and enforces countermeasures, including stake slashing or transaction throttling.Implemented on Ethereum, the solution demonstrates improved network resilience with minimal overhead, offering a decentralized and scalable defense against pollution threats while preserving data integrity.
Abstract The breaches of the blockchain wallet keys greatly harm the security of blockchain transactions. To protect the secret keys, the known solutions, such as hierarchical deterministic wallets proposed in BIP32 or stealth addresses adopted in Monero, have been extensively researched. However, most of the existing works assume the key is safe, in the sense that it cannot be stolen or damaged, which is not true in practice. Moreover, current key revocation mechanisms either rely on centralized authorities, compromising decentralization, or require economic incentives to ensure nodes remain consistantly online. In this paper, we introduce Cocoon, the first blockchain wallet scheme that supports stealth addresses and provides a wallet revocation mechanism without the need for certificates. Cocoon not only ensures the privacy of wallet secret keys but also can individually revoke compromised keys with high performance. Our contributions are three-fold: First, we present the formal model and the related security definitions. Next, we give a generic construction based on the hierarchical identity-based signature, identity-based key encapsulation mechanism and non-interactive zero-knowledge proof. We then extend the scheme to the hierarchical setting for diverse scenarios. Finally, we give the implementation, and the results show that the scheme is practical.
NFT (Non-Fungible Token) has considerable potential in the field of intellectual property. It can not only improve the efficiency of copyright registration but also promote the improvement of transaction transparency and liquidity. However, existing copyright protection schemes of NFT image relied on the NFTs itself minted by third-party platforms. Also, the widespread use of NFTs has introduced new complexities to copyright protection due to their unique nature. Therefore, we have proposed a multi-layered blockchain security framework to resolve security vulnerabilities by protecting users from threats such as illegal copying, intellectual property rights infringement, and malware infection that may occur during the process of acquiring NFT assets through analysis of smart contracts, metadata, and digital assets that constitute NFTs.
The emergence of decentralized file-sharing platforms has introduced new challenges in ensuring secure data transmission, preserving node reputation, and preventing unauthorized access. This study presents an advanced peerto-peer (P2P) file-sharing system that integrates encrypted communication channels with blockchain-based consensus mechanisms to strengthen data confidentiality and trust evaluation. By employing protocols such as Proof-of-Work (PoW) and Proof-of-Stake (PoS), the proposed architecture establishes a tamper-resistant and verifiable ledger of interactions. Cryptographic techniques are used to protect data in transit and maintain privacy-preserving trust scores without revealing user identities. The system's reputation module continuously aggregates behavioural metrics, adjusting trust values through dynamic weighting and anomaly detection. Experimental evaluation demonstrates that this approach achieves high resilience against Sybil and eavesdropping attacks while preserving the integrity and confidentiality of shared content. The proposed model offers a scalable and secure foundation for next-generation decentralized file-sharing systems.
This study investigates the economic efficiency and market behavior of Bitcoin and Ethereum, the two largest cryptocurrencies by market capitalization.Utilizing daily data from August 7, 2016, to February 15, 2023, the research employs the Adjusted Market Inefficiency Magnitude (AMIM) measure and quantile regression analysis to assess time-varying efficiency levels and identify influencing factors.Findings indicate that both markets exhibit periods of efficiency and inefficiency, with Bitcoin demonstrating higher efficiency levels than Ethereum.Key drivers of market inefficiency include global financial stress, liquidity, and the COVID-19 pandemic.The study contributes to understanding the dynamic nature of cryptocurrency markets and provides insights for investors and policymakers.
Blockchain or Distributed Ledger Technologyβs (DLT) disruptive architecture will revolutionise both economic activity and social structure. Institutional crypto economics is a new analytic framework for studying that evolutionary process in general, and bitcoin in particular, it presents us with a new method of organising the world, just like the Internet did. Bitcoin will have a similar effect on economy, money and finance. Developing countries face multiple problems such as lack of financial services and infrastructure (road, railways, telecommunication, and others). The disruptive architecture of Blockchain or Distributed Ledger Technology is well suited to benefit developing countries. This will be clearly visible in the implementation and application of Internet of Things (IoT) in emerging services. The nature of innovation in service-sector-based technology in developing countries differs, and the nature of IoT as a potentially disruptive emergent service product technology enabler emphasises this difference. The conventional productprocess innovation divide may no longer be applicable: the true value in IoT rests in neither. It is present in the system as well as the data collected by all devices everywhere in the world. The services income, which is generated by a combination of intelligent apps, analytics, and system integration services, represents a considerably greater revenue possibility for both developers and consumers of IoT enabled use cases. This paper presents how a peer-to-peer network that provides coverage for low-power IoT devices bringing a new viewpoint to the cellular telecommunications market. The network is a decentralised IoT infrastructure that is built on a Blockchain or Directed Acyclic Graph (DAG) by the people, communities, and individuals to offer hotspots wireless to the communities that help creates opportunities in financial freedom, helps supply chains traceability, forestry control and others. The paper demonstrates that decentralised IoT networks based on Tangle DAG can reduce infrastructure costs by 35-40% while increasing wireless coverage by 60%, with 1.5 million devices per 100 hotspots. It makes a unique and significant contribution to the deployment of IoT on Blockchain or Distributed Ledger Technology, as well as its potential to reduce poverty by improving the effectiveness and efficacy of existing procedures in various sectors of developing countries.
Non-fungible tokens (NFT) have recently become a popular method of tokenizing \& commercializing personal artifacts. Designing NFTs requires selecting different blockchain-based consensus models, encryption techniques, and distribution mechanisms. Existing NFT design techniques use computationally complex encryption models like Elliptic Curve Cryptography (ECC), Advanced Encryption Standard (AES), etc., which restricts their general-purpose usability, limiting their scalability for real-time use cases. To overcome this drawback, while maintaining high security, this text proposes a design of a lightweight, restrictive non-fungible token based on Practically Unclonable Functions (PuFs) via image signature patterns. The proposed model initially collects context-specific information sets about the entity that needs tokenization and uses this information to generate restrictive hash sets. These hash sets are passed through a customized PuF model, which generates image-like hash signatures. The generated hash signatures are iteratively embedded into unique images, which are fused via a dual visual encryption-decryption process. The encryption process generates 2 image sets, for distribution among the buyer \& seller, while the decryption process aggregates these image sets to form a single file token. These tokens are passed through another encryption-decryption-based validation process while reselling operations. Due to use of PuFs and restrictive hash sets, the proposed model is capable of deployment for low-power IoT applications and can be scaled for general-purpose scenarios. The proposed model was tested on different NFT use cases, and showcased 10.4% lower processing delay, 8.3% lower energy consumption during selling, and 4.9% lower energy consumption during reselling processes. The tokens generated via this model were also tested under different attack types, and similar efficiency levels were observed under real-time scenarios.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
We consider the problem of a game theorist analyzing a game that uses cryptographic protocols. Ideally, a theorist abstracts protocols as ideal, implementation-independent primitives, letting conclusions in the "ideal world" carry over to the "real world." This is crucial, since the game theorist cannot--and should not be expected to--handle full cryptographic complexity. In today's landscape, the rise of distributed ledgers makes a shared language between cryptography and game theory increasingly necessary. The security of cryptographic protocols hinges on two types of assumptions: state-of-the-world (e.g., "factoring is hard") and behavioral (e.g., "honest majority"). We observe that for protocols relying on behavioral assumptions (e.g., ledgers), our goal is unattainable in full generality. For state-of-the-world assumptions, we show that standard solution concepts, e.g., ($Ξ΅$-)Nash equilibria, are not robust to transfer from the ideal to the real world. We propose a new solution concept: the pseudo-Nash equilibrium. Informally, a profile $s=(s_1,\dots,s_n)$ is a pseudo-Nash equilibrium if, for any player $i$ and deviation $s'_i$ with higher expected utility, $i$'s utility from $s_i$ is (computationally) indistinguishable from that of $s'_i$. Pseudo-Nash is simpler and more accessible to game theorists than prior notions addressing the mismatch between (asymptotic) cryptography and game theory. We prove that Nash equilibria in games with ideal, unbreakable cryptography correspond to pseudo-Nash equilibria when ideal cryptography is instantiated with real protocols (under state-of-the-world assumptions). Our translation is conceptually simpler and more general: it avoids tuning or restricting utility functions in the ideal game to fit quirks of cryptographic implementations. Thus, pseudo-Nash lets us study game-theoretic and cryptographic aspects separately and seamlessly.
The volatility and complex dynamics of cryptocurrency markets present unique challenges for accurate price forecasting. This research proposes a hybrid deep learning and machine learning model that integrates Long Short-Term Memory (LSTM) networks and Extreme Gradient Boosting (XGBoost) for cryptocurrency price prediction. The LSTM component captures temporal dependencies in historical price data, while XGBoost enhances prediction by modeling nonlinear relationships with auxiliary features such as sentiment scores and macroeconomic indicators. The model is evaluated on historical datasets of Bitcoin, Ethereum, Dogecoin, and Litecoin, incorporating both global and localized exchange data. Comparative analysis using Mean Absolute Percentage Error (MAPE) and Min-Max Normalized Root Mean Square Error (MinMax RMSE) demonstrates that the LSTM+XGBoost hybrid consistently outperforms standalone models and traditional forecasting methods. This study underscores the potential of hybrid architectures in financial forecasting and provides insights into model adaptability across different cryptocurrencies and market contexts.
H. Mohammed Ali, William J. Buchanan, Jawad Ahmad, Mwrwan Abubakar Β· 6 authors
We introduce TrustShare, a novel blockchain-based framework designed to enable secure, privacy-preserving, and trust-aware cyber threat intelligence (CTI) sharing across organizational boundaries. Leveraging Hyperledger Fabric, the architecture supports fine-grained access control and immutability through smart contract-enforced trust policies. The system combines Ciphertext-Policy Attribute-Based Encryption (CP-ABE) with temporal, spatial, and controlled revelation constraints to grant data owners precise control over shared intelligence. To ensure scalable decentralized storage, encrypted CTI is distributed via the IPFS, with blockchain-anchored references ensuring verifiability and traceability. Using STIX for structuring and TAXII for exchange, the framework complies with the GDPR requirements, embedding revocation and the right to be forgotten through certificate authorities. The experimental validation demonstrates that TrustShare achieves low-latency retrieval, efficient encryption performance, and robust scalability in containerized deployments. By unifying decentralized technologies with cryptographic enforcement and regulatory compliance, TrustShare sets a foundation for the next generation of sovereign and trustworthy threat intelligence collaboration.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Design thinking is an important tool for connecting innovation ability with practical problems. Design thinking, as a systematic approach to thinking concepts, processes, and learning tools, can provide new ideas for educational reform and the cultivation of talents in the future. Introducing design thinking into higher education and establishing an effective and innovative curriculum system is also aimed at better cultivating innovative talents. Based on the characteristics of blockchain technology such as decentralization, security and equality, this study builds a platform for design thinking education and expounds the practical problems such as the lack of thinking enthusiasm and motivation of students in the existing education model and the transformation of theory into practice. Analyze the possibility that blockchain technology can help students stimulate their creativity through incentive mechanisms, protect students' design achievements through distributed ledgers, and enhance their employment competitiveness. While blockchain technology makes it easier for colleges and universities to implement design thinking education, it also gives them new ideas and opportunities to implement creative teaching based on design principles, creates an equitable and effective learning environment for students, and gives them access to a better learning platform.
With the development of educational modernization, digital technology has become a key force driving educational progress. As a decentralized, secure and reliable technology, blockchain has application potential in educational resource management, information management and the construction of basic platforms. At present, the cross-disciplinary integration in design faces many challenges, such as the problem of disciplinary barriers, the difficulty in protecting resource property rights, technical obstacles, the high cost of resource sharing, and the lack of a dynamic monitoring and evaluation system, etc. This paper studies the connotation, characteristics of blockchain and its coupling in interdisciplinary integration, designs an interdisciplinary integration resource platform based on blockchain, including network architecture, functions, learning coins and supply levels. This platform, through technological approaches such as distributed ledgers and smart contracts, enhances the effectiveness of cross-disciplinary integration, improves the level of copyright protection, reduces sharing costs, and realizes the automated operation of the regulatory system, providing new ideas and practical methods for the high-quality development of design education.
This paper introduces a comprehensive architectural framework for quantum-resistant health data management. The proposed Immutable Health Ledger (IHL) represents a fundamental paradigm shift an advanced Zero-Trust architecture engineered to withstand both current cyber threats and the emerging challenges posed by quantum computing, which are expected to render existing encryption standards obsolete. The IHL ensures provable data sovereignty through three foundational principles: a Biometric Trust Anchor in which patient identity serves as the cryptographic root of trust; a Post-Quantum Cryptographic Foundation built upon NIST-standardized algorithms with a hybrid deployment strategy; and a Distributed Integrity Layer that makes any form of data manipulation computationally and economically impractical. This document presents the complete mathematical formulations, formal security proofs, performance analyses, and an implementation roadmap that together define the operational and theoretical integrity of the proposed system.
The article examines the integration of blockchain technology and smart contracts into the sphere of civil law relations, focusing on legal consequences and emerging problems related to their application. As these technologies continue to transform various sectors, including finance, supply chain management, and the real estate market, the need for appropriate legal regulation is becoming increasingly urgent. The purpose of this article is to comprehensively analyze the use of blockchain and smart contracts in civil law relations and to study legal issues, current judicial practice, and various regulatory approaches in different jurisdictions. The research is based on an interdisciplinary approach that combines elements of legal analysis, comparative law, as well as the study of modern digital technologies. By examining the intersection of these advanced technologies with established legal principles, the author aims to illuminate the evolving landscape of digital agreements and their consequences for civil law in the 21st century. Assessing the importance of international cooperation for the formation of cross-border legal standards, as well as the prospects and challenges of further development, this study allows for an understanding of the emerging legal landscape of blockchain technologies in the civil law sphere.
Mohamed Mahmoud Alkabir, Mohamed Taher R Nashnosh, Tarek Ayad H Shaladi
6G wireless networks introduce revolutionary features beyond 5G by providing human-focused services and extended IoT battery life and holographic telepresence and tactile Internet capabilities. 6G enables terahertz (THz) spectrum together with pervasive AI and intelligent spectrum management to deliver unmatched reliability and complete 3D coverage. The AI-native architecture and distributed intelligence of 6G networks create new security risks because they make systems more vulnerable to adversarial attacks and scalability limitations. A Swarm Intelligence-Driven Collaborative Intrusion Detection System (CIDS) for 6G-IoT networks addresses security challenges through the combination of ant colony optimization (ACO) with Edge Blockchain for decentralized adaptive threat detection. The framework includes three main components: (1) autonomous ant agents spread anomaly signatures through pheromone trails and (2) lightweight Hyperledger Fabric provides tamper-proof logging of threat intelligence and (3) smart contracts execute mitigation actions based on dynamic trust threshold values. The 50-node UAV-ground sensor testbed results show that the system detects DDoS attacks with 98.7% accuracy while achieving 47% lower latency than federated learning baselines and 73% storage efficiency through IPFS-backed hashing. The system decreases false positives by 62% while maintaining blockchain transaction rates of 420 per second at large scales. The proposed framework swarm intelligence with distributed ledger technology solves essential 6G security challenges regarding autonomy and scalability and resilience which enables trustworthy AI-driven networks.
This systematic meta-review analyzes over 75 papers (2020-2025) applying deep learning (DL) techniques to cryptocurrency trading, adhering to PRISMA guidelines. It evaluates various DL architectures, including LSTM, GRU, CNN, and Transformers, and finds that DL methods outperform traditional approaches in managing the high volatility and non-linear patterns of crypto markets. Key findings highlight the promise of hybrid and ensemble models, the benefits of integrating blockchain data, sentiment analysis, and macroeconomic factors for improved predictions, and the potential of deep reinforcement learning for developing autonomous trading strategies with risk-adjusted returns. However, challenges such as model interpretability, nonstationary data, and real-world deployment persist. The review emphasizes emerging directions like explainable AI (XAI) for transparent decision-making and high-frequency trading applications, providing a critical synthesis of methodologies, empirical results, and research gaps to inform both academic research and practical trading system development.