Autonomous technology has advanced rapidly in recent years, with intelligent systems demonstrating increasingly sophisticated capabilities in perception, decision-making, and adaptive behavior. These advancements have positioned autonomous agents to be teammates, enabling collaboration with humans in diverse domains and prompting emergence of Human-Autonomy Teaming (HAT) systems. HAT systems increasingly involve multiple autonomous agents working alongside humans in dynamic, high-stakes environments. HAT systems are often engineered with static hierarchical structures that predefine leadership authority for a set of tasks, thereby constraining their adaptability to shifting situational demands or unanticipated conditions, resulting in unintended degradation of collaboration and task performance. For dynamic environments, HAT systems require flexible or emergent leadership structures between agents. This dissertation investigates shared leadership for enabling flexible authority distribution between human and autonomous agents to enhance collaboration and performance in multi-agent systems composed of human and autonomous agents. The objectives of this research were (1) to understand how shared leadership functions in human teams can be adapted for multi-agent HAT systems, (2) to model leadership emergence from the human's perspective and identify factors governing the temporal patterns, and (3) to compare performance and perceived team dynamics between shared leadership and centralized leadership. vspace{0.1in} newline Study 1 was a systematic literature review of shared leadership in human teams for deriving mechanisms that can be engineered into HAT. The review revealed that humans rely on interpersonal trust and performance-based competence assessments for leadership distribution, with decentralization and mutual influence as the most influential mechanisms for enabling sharing leadership. The review also identified questionnaire-based assessments and network analysis as viable measurement approaches, with the latter also a viable approach for implementing shared leadership in HAT. These findings established the theoretical and methodological foundation for operationalizing and assessing shared leadership in HAT. Study 2 was an experiment recruiting human participants to complete a series of object-recognition tasks which involved assignments of multiple unmanned aerial vehicles (UAVs) in a simulated search and rescue context. Modeling the experimental data using network analysis, specifically in how the human's trust-competence perceptions of the autonomy evolve over time, revealed temporal patterns of leadership assignment. The study included the Trust-Competence-Identity Network (TCIN) that was developed to capture the humans' perception of agents across repeated task iterations. Logistic regression at the population level demonstrated that competence functioned as a capability-based predictor, while temporal exponential random graph models at the individual levels demonstrated that trust operated as an individualized experience-driven factor for predicting leadership assignment. The results provided foundational evidence supporting TCIN in predicting leadership emergence in HAT, illustrating the co-variation of key factors in human selection of autonomous agents as the leader. Study 3 was another experiment recruiting human participants to complete a series of object-recognition tasks that included conditions of the traditional centralized leadership and shared leadership for comparison of performance in multi-agent HAT. Study 3 also included a newly developed shared leadership questionnaire for HAT, adapted from validated instruments in human teams to measure leadership dynamics in HAT. Shared leadership demonstrated superior performance compared to centralized leadership, suggesting that distributing authority between humans and autonomous agents produces better outcomes than concentrating authority. Logistic regression at the population level demonstrated that trust moderated the rate at which complementary claiming-granting increased, while temporal exponential random graph models at the individual levels demonstrated that participants ultimately adopted complementary patterns. The shared leadership questionnaire also revealed that participants perceived more leadership distribution, team collaboration, and deference to expertise under shared leadership than the centralized leadership condition. These findings demonstrate that shared leadership in HAT involves both temporal learning processes and recognition of functional benefits that transcend individual differences in agent evaluation, establishing shared leadership as a viable organizational structure for multi-agent teams.
Non-Fungible Tokens (NFTs) represent a revolutionary class of digital assets, characterized by their uniqueness and value derived from metadata and visual traits. However, NFT markets suffer from volatility and a lack of transparent valuation systems, making it difficult for collectors and investors to estimate asset worth. This paper presents a comprehensive machine learning pipeline for predicting the market value of NFTs based on trait rarity and sale metadata. We apply rigorous preprocessing, compute rarity scores from trait distributions, and compare multiple regression models, including Random Forest, LightGBM, CatBoost, and Extra Trees. Our analysis demonstrates that tree-based models significantly outperform simpler regressors, with Extra Trees achieving the lowest RMSE of 136.91 and the highest$\mathrm{R}^{\mathrm{2}}$score of$\text{1. 0}$. Visual and statistical analyses further validate the effectiveness of our methodology in predicting NFT prices with high precision.
Michele Fabi, Viraj Nadkarni, Leonardo Leone, Matheus V. X. Ferreira
<div> We develop an axiomatic theory for Automated Market Makers (AMMs) in local energy sharing markets and analyze the Markov Perfect Equilibrium of the resulting economy with a Mean-Field Game. In this game, heterogeneous prosumers solve a Bellman equation to optimize energy consumption, storage, and exchanges. Our axioms identify a class of mechanisms with linear, Lipschitz continuous payment functions, where prices decrease with the aggregate supply-to-demand ratio of energy. We prove that implementing batch execution and concentrated liquidity allows standard design conditions from decentralized finance-quasi-concavity, monotonicity, and homotheticity-to construct AMMs that satisfy our axioms. The resulting AMMs are budget-balanced and achieve ex-ante efficiency, contrasting with the strategy-proof, expost optimal VCG mechanism. Since the AMM implements a Potential Game, we solve its equilibrium by first computing the social planner's optimum and then decentralizing the allocation. Numerical experiments using data from the Paris administrative region suggest that the prosumer community can achieve gains from trade up to 40% relative to the grid-only benchmark. </div>
In decentralized finance (DeFi), designing fixed-income lending automated market makers (AMMs) is extremely challenging due to time-related complexities. Moreover, existing protocols only support single-maturity lending. Building upon the BondMM protocol, this paper argues that its mathematical invariants are sufficiently elegant to be generalized to arbitrary maturities. This paper thus propose an improved design, BondMM-A, which supports lending activities of any maturity. By integrating fixed-income instruments of varying maturities into a single smart contract, BondMM-A offers users and liquidity providers (LPs) greater operational freedom and capital efficiency. Experimental results show that BondMM-A performs excellently in terms of interest rate stability and financial robustness.
Damilare E. Bakare, Adekemi Olawunmi Amoo, Mary T. Onifade
The health insurance sector has been facing many challenges recently, such as fraudulent activities in insurance claims, data breaches, and high transaction costs, particularly with existing systems built on the Ethereum network, which negatively affect its efficiency and effectiveness.These challenges undermine the trust and financials of insurance providers while compromising the privacy of the patient's health records.To address this issue, this study proposes a conceptual framework that uses zero-knowledge proof within the blockchain system and is deployed on the Polygon Network for its low transaction fees and higher throughput.The proposed model allows the verification of an insurance claim without revealing sensitive patient health records, ensuring privacy while preventing fraudulent activities.In this conceptual design, the hospital can issue verifiable proof of treatment, appointment, and bill that shows the validity of the insurance claim without revealing the underlying health record to the insurer.This study, therefore, contributes to supporting research in decentralized applications for healthcare insurance by presenting a conceptual model and comprehensively analyzing the feasibility, rather than a full-scale implementation.It also emphasizes the need to preserve privacy in sensitive domains and the potential benefits of blockchain and ZKP integration.In conclusion, the research's findings show that, in theory, integrating ZKP with blockchain technology can enhance healthcare insurance processes in terms of reliability, efficiency, privacy, and security.However, further research and practical development are required to realize and evaluate a fully operational system.
This study aims to analyze the influence of performance-based reward systems and decision decentralization on innovation in human resource management. In an era of increasingly dynamic global competition, organizations are required not only to carry out HRM functions efficiently but also to adopt innovative approaches to address challenges posed by the work environment, technology, and employee expectations. A performance-based reward system, which directly links rewards to individual or team performance, can motivate employees to engage in innovative behavior, while decision decentralization allows for faster decision-making and greater responsiveness to local needs. This study used a quantitative approach with a survey method to collect data from structural and functional officials in six Makassar City government agencies that implement a performance-based reward system and decision decentralization. The results indicate that both variables have a positive effect on HRM innovation, both separately and simultaneously. These findings provide theoretical and practical insights into the importance of integrating a fair and transparent reward system with a more autonomous decision-making structure in encouraging innovation in human resource management. Policies that encourage these two elements can strengthen competitive advantage and organizational performance.
Digital product passports outline information about a product’s lifecycle, circularity, and sustainability-related data. Sustainability data contains claims about carbon footprint, recycled material composition, ethical sourcing of production materials, etc. Also, upcoming regulatory directives require companies to disclose this type of information. However, current sustainability reporting practices face challenges, such as greenwashing, where companies make incorrect claims that are difficult to verify. There is also a challenge of disclosing sensitive production information when other stakeholders, such as consumers or other economic operators, wish to verify sustainability claims independently. Zero-knowledge proofs (ZKPs) provide a cryptographic system for verifying statements without revealing sensitive information. The goal of this research paper is to explore ZKP cryptography, trust models, and implementation concepts for extending DPP capability in privacy-aware reporting and verification of sustainability claims in products. To achieve this goal, first, formal representations of sustainability claims are provided. Then, a data matrix and trust model for generating proofs are developed. An interaction sequence is provided to show different components for various proof generation and verification scenarios for sustainability claims. Lastly, the paper provides a circuit template for the proof generation of an example claim and a credential structure for their input data validation. The proposed approach is assessed using a scenario-based evaluation to check the performance metrics for data credential verification and proof generation for verifying material composition in a product.
Open access
2 source records
Physical Unclonable Functions (PUFs) and Hardware Security
Tuan-Dung Tran, Bao Huynh, Tra Minh Trong, Tong Thuan Nguyen · 6 authors
Permissioned blockchains using Proof-ofAuthority (PoA) deliver high throughput but face issues of predictability and centralization, while token-weighted governance risks plutocracy that undermines fairness. This paper proposes Proof-of-Merit (PoM), a consensus and governance framework that integrates PoA with Verifiable Random Functions (VRFs) and a dual-token model. PoM selects validators through a weighted combination of transferable stake (UIT-Coin) and non-transferable academic reputation (UIT-Rep), earned via verifiable onchain learning activities. Governance follows the same principle, anchoring voting rights in Sybil-resistant merit rather than pure capital. To ensure sustainability, PoM introduces reputation decay, preventing long-term power concentration and promoting continuous participation. We implement PoM on Hyperledger Besu and evaluate it with Hyperledger Caliper. Results show PoM achieves strong performance while significantly improving fairness, with a much lower Gini coefficient and higher Nakamoto coefficient compared to IBFT 2.0. Sensitivity analysis further highlights the need for dynamic reputation mechanisms to avoid saturation. These contributions establish PoM as a scalable, equitable, and sustainable foundation for Learn-to-Earn ecosystems, where influence derives from ongoing educational engagement instead of wealth accumulation.
The contemporary art world is undergoing a foundational shift, driven by the emergence of blockchain technology and its most culturally salient application: Non-Fungible Tokens (NFTs). This transition marks a move from the physical, gatekept spaces of the "White Cube" gallery to the distributed, code-governed networks of the blockchain ledger. This article argues that this is not merely a change in the medium of art's financialization, but a profound process of decentralization reshaping the core pillars of the art ecosystem-curation, valuation, ownership, and access. We analyze how blockchain disrupts traditional, centralized art market models by enabling peer-to-peer transactions, immutable provenance tracking, and fractional ownership through smart contracts. Crucially, we examine the rise of algorithmic and community-driven curation, where platforms like SuperRare or DAOs (Decentralized Autonomous Organizations) challenge the authority of the traditional curator-institution. A conceptual framework (Figure 1) maps this new ecosystem, while a comparative table (Table 1) delineates the paradigm shifts across key domains. Through case studies of NFT platforms, crypto-art movements, and artist collectives, we demonstrate both the emancipatory potential and the critical tensions within this decentralization. We conclude that while blockchain introduces new forms of transparency, accessibility, and artist empowerment, it simultaneously engenders novel hierarchies, environmental concerns, and questions about the nature of cultural value in a digitally native era. The future of visual culture will be negotiated in the space between the aesthetic aura and the verifiable hash.
Vehicular ad-hoc networks (VANETs) play a vital role in enhancing modern transportation systems, facilitating real-time data exchange in dynamic environments. However, VANETs face challenges such as limited range and interference in dense areas. This paper introduces an unmanned aerial vehicle (UAV)-aided reputation-based cluster routing (URCR) protocol to address issues such as improving data transmission, reducing delay, and lowering hop count. The proposed URCR protocol utilizes VANET clustering, UAV-aided communication, and a Proof-of-Stake based cluster head-toggling algorithm to achieve balanced energy consumption. Blockchain-based reputation management is integrated into the protocol to evaluate the trustworthiness of the member nodes and prevent malicious behavior in the VANET. Simulations using Network Simulator 3 show that URCR improves the average hop count by 47.6% and 15.2%, the packet delivery ratio by 22.9% and 4.3%, and the end-to-end delay by 48.8% and 22.3%, compared to drone-assisted cooperative routing (DACR) and VANET routing with UAV assistance (VRU), respectively.
The rapid evolution of digital assets transforms cryptocurrencies into one of the most volatile and data-rich financial markets. Their nonlinear and unpredictable nature limits the effectiveness of traditional forecasting models, motivating the use of machine learning methods to identify hidden patterns and short-term price movements. This study compares the performance of Logistic Regression (LR), Random Forest (RF), XGBoost, Support Vector Classifier (SVC), K-Nearest Neighbors (KNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) models in predicting the daily price directions of Bitcoin (BTC), Ethereum (ETH), and Ripple (XRP). Extensive data preprocessing and feature engineering are performed, integrating a broad set of technical indicators to enhance model generalization and capture temporal market dynamics. The results show that XGBoost achieves the highest classification accuracy of 55.9% for BTC and 53.8% for XRP, while LR provides the best result for Ethereum with an accuracy of 54.4%. In trading simulations, XGBoost achieves the strongest performance, generating a cumulative return of 141.4% with a Sharpe ratio of 1.78 for Bitcoin and 246.6% with a Sharpe ratio of 1.59 for Ripple, whereas LSTM delivers the best results for Ethereum with a 138.2% return and a Sharpe ratio of 1.05. Compared to recent studies, the proposed approach attains slightly higher accuracy, while demonstrating stronger robustness and profitability in practical backtesting. Overall, the findings confirm that through rigorous preprocessing machine learning-based strategies can effectively capture short-term price movements and outperform the conventional buy-and-hold benchmark, even under a simple rule-based trading framework.
Probate stands as a bastion of legal formalism, seemingly resistant to the transformative currents of digital innovation that have swept through other domains of American law. While financial transactions, real property conveyances, and contract execution have increasingly begun exploring the use of Web3 technologies such as blockchain and smart contracts, estate and probate law remain tethered to paper-based procedures and rigid execution requirements. Nevada was the first state to provide legal support for Web3 technology, amending its Uniform Electronic Transactions Act statutes in 2017 to recognize blockchain-based transactions as valid and judicially enforceable. Yet despite this progressive legislative framework, the state’s estate and probate laws remain unchanged. What reforms are required to extend this legal recognition of blockchain to testamentary instruments and probate administration? To explore this, I begin in Part I by examining Nevada’s existing statutory framework for traditional paper wills, electronic wills, and probate administration, identifying where these laws diverge from the state’s more progressive legislation governing blockchain-based transactions. In Part II, I introduce the concept of a blockchain will, explain its technical functionality, and discuss how such instruments can be amended, revoked, or rendered obsolete. I then propose specific legislative reforms that could allow blockchain wills to serve as legally recognized alternatives to traditional paper wills, including the creation of a state-managed blockchain will registry that would provide the procedural infrastructure for securely filing, validating, and preserving blockchain wills. To illustrate how these proposals might operate in practice, hypothetical examples modeling blockchain-based testamentary execution and probate are included. Finally, I analyze the policy considerations both for and against reform, examining the legal barriers that must be addressed and the potential benefits this technology could bring to probate courts.
Ashwag Alotaibi, Huda Aldawghan, M. M. Hafizur Rahman
This study summarizes the body of research on the IoT and NFTs overlap, highlighting important security concerns, the function of blockchain technology, and implications for future study and smart environment applications. IoT devices provide creative solutions that boost operational effectiveness and enhance user experiences as they spread throughout different sectors. But there are also serious drawbacks to this expansion, especially in terms of security and privacy. At the same time, NFTs unique digital assets verified by blockchain technology—have become extremely popular because of their unique features and wide range of uses. This paper carefully looks at how security frameworks in digital ecosystems may be impacted by the integration of IoT and NFTs. The results emphasize how urgently this integration must be studied further to minimize new risks and maximize the advantages of IoT and NFTs across a variety of sectors. The study intends to contribute to a more secure and effective IoT ecosystem by examining the difficulties presented by this integration. Contributing to the development of a more robust and secure IoT ecosystem is the ultimate aim of this research. This study aims to open the door for future developments that optimize the benefits between the two technologies while reducing risks by recognizing and evaluating the difficulties brought about by the integration of IoT and NFTs. Both academics and industry stakeholders navigating the rapidly changing IoT and blockchain world will find great significance in the results of this research.
David Arroyo, Rafael Mata Milla, Marc Almeida Ros, Nikolaos Lykousas · 7 authors
Crime as a Service (CaaS) has evolved from isolated criminal incidents to a broad spectrum of illicit activities, including social media manipulation, foreign information manipulation and interference (FIMI), and the sale of disinformation toolkits. This article analyses how threat actors exploit specialised infrastructures ranging from proxy and VPN services to AI-driven generative models to orchestrate large-scale opinion manipulation. Moreover, it discusses how these malicious operations monetise the virality of social networks, weaponise dual-use technologies, and leverage user biases to amplify polarising narratives. In parallel, it examines key strategies for detecting, attributing, and mitigating such campaigns by highlighting the roles of blockchain-based content verification, advanced cryptographic proofs, and cross-disciplinary collaboration. Finally, the article highlights that countering disinformation demands an integrated framework that combines legal, technological, and societal efforts to address a rapidly adapting and borderless threat
As the Ethereum platform continues to mature and gain widespread usage, it is crucial to maintain high standards of smart contract writing practices. While bad practices in smart contracts may not directly lead to security issues, they elevate the risk of encountering problems. Therefore, to understand and avoid these bad practices, this paper introduces the first systematic study of bad practices in smart contracts, delving into over 47 specific issues. Specifically, we propose SCALM, an LLM-powered framework featuring two methodological innovations: (1) A hybrid architecture that combines context-aware function-level slicing with knowledge-enhanced semantic reasoning via extensible vectorized pattern matching. (2) A multi-layer reasoning verification system connects low-level code patterns with high-level security principles through syntax, design patterns, and architecture analysis. Our extensive experiments using multiple LLMs and datasets have shown that SCALM outperforms existing tools in detecting bad practices in smart contracts.
Chaoming Shi, Haomeng Xie, Zheng Yan, Laurence T. Yang
Blockchain is a decentralized ledger with a secure and immutable chain structure. The advanced attributes of blockchain, including decentralization, anonymity, transparency, and zero trust support, have positioned it as a transformative technology across different areas of expertise, like medicine, finance, and the Internet of Things (IoT). Nonetheless, blockchain’s progress has been constrained in various aspects, revealing inefficiency, privacy, high transaction fees, and challenges with on-chain storage. To address these limitations, off-chain technology has emerged as a solution by moving computation and storage overhead away from the blockchain. However, a comprehensive survey on off-chain schemes is lacking in the current literature. In this article, we conduct a thorough survey on off-chain technologies. We first introduce the fundamental concepts and characteristics of both blockchain and off-chain technologies. Furthermore, we establish a thorough taxonomy of off-chain technologies based on distinct application scenarios. We put forth a series of evaluation criteria, based on which we seriously review and analyze the existing off-chain schemes to assess their strengths and limitations. Conclusively, we outline a list of open issues and propose promising future research directions based on our thorough review and analysis on off-chain technologies.
Dynamiczny rozwój technologii rozproszonych rejestrów (DLT – Distributed Ledger Technology) oraz rosnące oczekiwania społeczne w zakresie transparentności finansów publicznych skłaniają do analizy możliwości wdrożenia technologii blockchain w systemie zarządzania wydatkami jednostek samorządu terytorialnego (JST). W artykule poddano ocenie potencjał blockchain jako narzędzia eliminującego asymetrię informacyjną i zwiększającego społeczną kontrolę nad finansami JST. Technologia ta, dzięki niezmienności rejestrów oraz kryptograficznemu potwierdzaniu transakcji, może przyczynić się do redukcji ryzyka korupcji i nadużyć budżetowych. Szczególną uwagę poświęcono aspektom prawnym implementacji blockchain w sektorze publicznym, w tym jego zgodności z ustawą o finansach publicznych, przepisami dotyczącymi zamówień publicznych oraz regulacjami RODO. W artykule przeprowadzono także analizę porównawczą międzynarodowych wdrożeń blockchain w administracji publicznej oraz zaproponowano model implementacji tej technologii w kontekście polskich JST.
The fisheries sector plays a critical role in Indonesia's economy. However, current implementations remain fragmented, leading to significant challenges in data reliability and verification. This fragmentation constrains cross-stakeholder verification and regulatory compliance across Aruna's ecosystem. Existing Enterprise Resource Planning (ERP) systems offer limited transparency and lack end-to-end certification workflows. This study proposes a blockchain-enabled traceability model that integrates an ERP system with QR-based verification technology to ensure verifiable provenance. Data were gathered through business-process mapping, systematic literature review, and in-depth stakeholder interviews. The model was evaluated and validated through online interview sessions with Aruna stakeholders to ensure practical applicability and business alignment. Smart contracts are utilized to automate critical batch creation, catch logging, quality control, role-based access control, and certification binding (SKP, HC, HACCP) to batch records. A QR interface enables on-demand access to verifiable batch histories for authorized internal users, regulators, buyers, and consumers. A proof-of-concept was implemented on a Polygon-compatible local Ethereum Virtual Machine (EVM) through sequential transactions. Stakeholder validation indicated that the model improved traceability integrity, reduced manual checks at handover points, and enhanced the credibility of certification data. By strengthening verifiable provenance, inclusion of small-scale fishers, and compliance efficiency within Aruna's ecosystem, the approach aligns with SDG 8 on decent work and economic growth and SDG 14 on life below water.
The research presents SmartProof as an artificial intelligence system which uses large language models and blockchain technology to create automated decentralized agreement generation and auditing and validation processes. SmartProof combines natural language code generation with AI security evaluation and IPFS-based decentralized storage and EIP-712 compliant digital signature functionality. The system enables users to develop smart contracts from high-level descriptions which then undergo automated verification before the system finishes the agreement process through blockchainbased verification of on-chain registration. The prototype system shows that AI-based contract creation tools shorten development periods and minimize programming mistakes and the multiagent auditing system identifies system weaknesses to generate trust-based risk assessment for deployment. The system achieves improved performance because it stores data outside the blockchain network and manages digital signatures which reduces gas costs and boosts system performance. SmartProof enables organizations to handle multiple agreements through one system which provides complete agreement transparency and complete security from contract inception to blockchain deployment.
P. Jeba Santhiya, Fackrudeen Ali Ahamed, Absalamova Gulmira Sharifovna, Christo Ananth · 6 authors
AQBCP is an Adaptive Quantum Byzantine Consensus Protocol that allows for trustless, scalable consensus in post-classical quantum blockchain systems. AQBCP has the capability of using hybrid quantum/classical methods (including dynamic pruning and quantum routing) to improve the reliability of its network and also improve how well it performs. AQBCP will have more than 50% BFT - which is greater than most classical algorithms - and can adapt to any changes in the network topological structure or the conditions of the quantum channels it uses. The analytical and simulation data shows AQBCP converges at a rate of O(log(n)), provides information theoretic security from classical and quantum enabled attacks and has better performance metrics for throughput and fault tolerance when run on current NISQ devices. The benchmarking of AQBCP with other post-quantum and quantum-classical protocols provides evidence that AQBCP is the best option and sets a base for future quantum secure distributed ledgers.
An open question recently posed by Fawzi and Ferme [IEEE Transactions on Information Theory 2024], asks whether non-signaling (NS) assistance can increase the capacity of a broadcast channel (BC). We answer this question in the affirmative, by showing that for a certainK-receiver BC model, called Coordinated Multipoint broadcast (CoMP BC) that arises naturally in wireless networks, NS-assistance provides multiplicative gains in both capacity and degrees of freedom (DoF), even achievingK-fold improvements in extremal cases. Somewhat surprisingly, this is shown to be true even for 2-receiver broadcast channels that are semi-deterministic and/or degraded. In a CoMP BC,Bsingle-antenna transmitters, supported by a backhaul that allows them to share data, act as oneB-antenna transmitter, to send independent messages toKreceivers, each equipped with a single receive antenna. A fixed and globally known connectivity matrix specifies for each transmit antenna, the subset of receivers that are connected to (have a non-zero channel coefficient to) that antenna. Besides the connectivity, there is no channel state information at the transmitter. The receivers have perfect channel knowledge. We show that NS-assistance has no DoF advantage in a fully connected CoMP BC. The DoF region is fully characterized for a class of connectivity patterns associated with tree graphs, for which the classical sum-DoF value is shown to be the number of leaf nodes, while the NS-assisted sum-DoF value is the total number of all (non-root) nodes. For arbitrary connectivity patterns, the sum-capacity with NS-assistance is bounded above and below by the min-rank and triangle number of the connectivity matrix, respectively, leading to matching bounds in many cases, e.g., if min(B,K) ≤ 6. While translations to Gaussian settings are demonstrated, for simplicity most of our results are presented under noise-free, finite-field (Fq) models. Converse proofs for classical DoF are found by adapting the Aligned Images bounds to the finite field model. Converse bounds for NS-assisted DoF/capacity extend the same-marginals property to the BC with NS-assistance available to all parties. Beyond the BC setting, even stronger (unbounded) gains in capacity due to NS-assistance are established for certain ‘communication with side-information’ settings, such as the fading dirty paper channel.
Blockchain is the root behind rise of cryptocurrencies. Blockchain minimizes the dependency of intermediaries that are required to accomplish a transaction, thus moving towards a more simplified procedure with reduced price and increased speed. It acts as a distributed ledger where each and every transaction or procedure is auditable and verified in real time. Once the data is recorded on the ledger then it can’t be altered later on. Along with rapid digitalization, the rise of cyber vulnerabilities can adversely impact organizations, resulting in detrimental outcomes. Organizations must be prepared with an effective cyber strategy so that they don’t fall prey to cybersecurity breach. Blockchain’s unique features can be considered as defensive wall that promotes robust workflow within the organizations against cyber attackers. Decentralization and enhanced security of blockchain can evolve the area of cybersecurity. Scalability is a substantial problem in blockchain. With the increase in total number of records, the block size also expands, that leads to slower verification procedure. Flaws in digital signatures, weak or inaccurate keys and incompetent encryption strength can result in critical security concerns. Downsides of transparent ledger should be considered to gain wider acknowledgment. In this chapter we will go through introduction to blockchain and cybersecurity, literature work conducted by different researchers in this domain, comparative analysis of different blockchain solutions, blockchain cybersecurity concerns, real-world case studies of this area, prevention of security issues of blockchain and conclusion.
In recent years, blockchain technology has gained considerable attention, with increasing interest in diverse fields, including banking, Retail, consumer products, Insurance, Real Estate, Government, healthcare, Supply Chain, and the automotive industry. Blockchain offers a secure, distributed database that can run without a central authority or administrator. Blockchain uses a distributed, peer-to-peer network called Digital Blocks to create a continuous, growing list of ordered records. Each transaction, represented in a cryptographically signed block, is then automatically authenticated by the network. Over time, however, it has become clear that the impact of blockchain as a technology is likely to be much broader than just the cryptocurrency domain and far deeper than simple distributed ledger storage. This detailed survey aims to summarize the most significant developments in blockchain implementation. This article will examine different domains where blockchain has been impacted and where implementation is expected in the future.