Madelaine Martinez Ferguson, Aliza Sharmin, Mustafa Can Camur, Xueping Li
This paper reviews intermodal transportation systems and their role in decarbonizing freight networks from an operations research perspective, analyzing over a decade of studies (2010-2024). We present a chronological analysis of the literature, illustrating how the field evolved over time while highlighting the emergence of new research avenues. We observe a significant increase in research addressing decarbonization since 2018, driven by regulatory pressures and technological advancements. Our integrated analysis is organized around three themes: a) modality, b) sustainability, and c) solution techniques. Key recommendations include the development of multistage stochastic models to better manage uncertainties and disruptions within intermodal transportation systems. Further research could leverage innovative technologies like machine learning and blockchain to improve decision-making and resource use through stakeholder collaboration. Life cycle assessment models are also suggested to better understand emissions across transportation stages and support the transition to alternative energy sources.
Mohammad Tabieh, Tala Qtaishat, Khaleda M Al Ghazawi, Ahmad Jamrah Ā· 7 authors
Expanding centralized wastewater services to all regions in Jordan is constrained by economic, topographical, and engineering challenges. As a result, decentralized wastewater treatment systems (DEWATS) are increasingly recognized as a complementary solution, particularly for rural and peri-urban areas where centralized connectivity is unfeasible. This study aims to design a sustainable and scalable business model for DEWATS in Jordan, with a focus on overcoming the institutional, financial, and regulatory barriers that have historically hindered their adoption. The research integrates spatial diagnostics, stakeholder consultations, institutional analysis, and a comprehensive financial and economic evaluation of three nature-based DEWATS configurations designed for settlements of up to 5,000 population equivalent (PE). Indicators such as average incremental cost (AIC), net present value (NPV), internal rate of return (IRR), and benefit-cost (B/C) ratios were used to evaluate technical and operational viability under both private and public investment scenarios. While all configurations demonstrated strong economic performance (IRRs > 27%, B/C > 3.7), financial feasibility remains weak without public capital support due to high per capita costs and limited revenue collection in small communities. The study identifies critical challenges, including undefined institutional mandates, lack of certified operators and regulators, insufficient cost-recovery mechanisms, and underdeveloped markets for private sector participation in O&M. Furthermore, existing tariff structures and bylaws do not adequately support capital investment or full operational cost recovery by private service providers. To address these gaps, the paper proposes a hybrid public-private-community business model incorporating performance-based service contracts, revised regulatory standards, and blended financing instruments. The model emphasizes the integration of DEWATS into spatial water safety planning, climate-resilient system design, and resource recovery to enhance environmental, social, and financial sustainability.
Distributed ledgers are common in the industry. Some of them can use blockchains as their underlying infrastructure. A blockchain requires participants to agree on its contents. This can be achieved via a consensus protocol. How do these protocols differ in performance, and how are the differences affected by the communication network? Moreover, such a protocol would need a timer to ensure progress, but how should the timer be set? This article presents an analytical model to address these and related issues when there are crash faults. Specifically, it focuses on two consensus protocols (Istanbul BFT and HotStuff) and two network topologies (Folded-Clos and Dragonfly). The model provides formulas that express the consensus time in terms of protocol and topology parameters. No other model in the literature provides such a global view of the parameter space. Analysis of the closed-form expressions yield new insights into how the timers should be set, how faults affect the consensus time, when one protocol is faster than the other, and how the two topologies differ in their impact. The formulas and analyses are validated with simulations. The conclusion also offers some tips for the analytical modeling of similar protocols.
The increasing urgency of climate change mitigation necessitates transparent and efficient carbon tracking mechanisms within global supply chains. Blockchain and the Internet of Things (IoT) present a synergistic approach to enhancing traceability, accountability, and automation in carbon emissions monitoring and reduction. Blockchainās decentralized and immutable ledger ensures data integrity, preventing fraud and manipulation, while IoT sensors provide real-time data collection on emissions, energy consumption, and supply chain activities. By integrating these technologies, organizations can achieve end-to-end visibility, ensuring compliance with environmental regulations and corporate sustainability goals. This paper explores the application of Blockchain and IoT in transparent carbon tracking and emission reduction across global supply chains. The study examines how blockchainās smart contracts enable automated verification of carbon credits and emissions data while ensuring secure and tamper-proof recordkeeping. IoT devices, including smart meters and carbon sensors, facilitate real-time emissions monitoring, allowing stakeholders to track and optimize energy usage. The combination of these technologies enhances supply chain transparency by enabling all participants, including manufacturers, logistics providers, and regulatory bodies, to access verifiable and auditable carbon data. Furthermore, the paper discusses the role of decentralized consensus mechanisms in validating emission records and preventing data manipulation. Blockchain-powered carbon trading platforms incentivize sustainable practices by enabling efficient carbon credit transactions. The integration of IoT and blockchain also fosters improved data interoperability, allowing seamless communication between diverse systems across different industries and regions. Challenges such as data privacy concerns, scalability limitations, and the high energy consumption of blockchain networks are examined, alongside potential solutions such as layer-2 scaling techniques and energy-efficient consensus protocols like Proof-of-Stake (PoS). The study concludes by presenting future research directions, emphasizing the need for standardized regulatory frameworks, enhanced interoperability solutions, and AI-driven analytics to optimize emissions management. By leveraging Blockchain and IoT, global supply chains can achieve greater transparency, efficiency, and sustainability, ultimately contributing to carbon footprint reduction and compliance with international climate policies. This paper provides a comprehensive analysis of the transformative potential of these technologies in driving environmentally responsible supply chain operations.
Fully Homomorphic Encryption over the torus (TFHE) enables computation on encrypted data without decryption, making it a cornerstone of secure and confidential computing. Despite its potential in privacy preserving machine learning, secure multi party computation, private blockchain transactions, and secure medical diagnostics, its adoption remains limited due to cryptographic complexity and usability challenges. While various TFHE libraries and compilers exist, practical code generation remains a hurdle. We propose a compiler integrated framework to evaluate LLM inference and agentic optimization for TFHE code generation, focusing on logic gates and ReLU activation. Our methodology assesses error rates, compilability, and structural similarity across open and closedsource LLMs. Results highlight significant limitations in off-the-shelf models, while agentic optimizations such as retrieval augmented generation (RAG) and few-shot prompting reduce errors and enhance code fidelity. This work establishes the first benchmark for TFHE code generation, demonstrating how LLMs, when augmented with domain-specific feedback, can bridge the expertise gap in FHE code generation.
As artificial intelligence (AI) becomes integral to microservices deployed across multi-cloud environments, ensuring secure and scalable observability is critical. Traditional centralized observability methods often fail to address the privacy, compliance, and performance challenges inherent to distributed AI systems. This paper presents a federated learningābased framework for AI observability that preserves data privacy and scalability across heterogeneous cloud platforms. The proposed framework decentralizes telemetry collection and analysis by integrating local observability agents with secure federated aggregation, while maintaining interoperability with modern DevOps pipelines. We evaluate the architecture through case studies in retail, healthcare, and finance sectors, demonstrating improvements in anomaly detection, regulatory compliance, and operational efficiency. Additionally, the paper examines ethical considerations such as data privacy, fairness, and transparency, and outlines future directions including edge observability, privacy-enhanced computation, and automated governance. This research provides a foundational strategy for building trustworthy and efficient observability systems tailored to AI-powered microservices within complex multi-cloud ecosystems. Traditional observability methods struggle with privacy and performance in AI-powered multi-cloud microservices. We propose a federated learningābased framework that enables decentralized telemetry monitoring while ensuring compliance and scalability. Our evaluation across healthcare, finance, and retail shows improvements in anomaly detection latency (25%), fraud detection accuracy (18%), and GDPR/HIPAA alignment. This work lays the groundwork for trustworthy and efficient AI observability in complex cloud-native ecosystems.
This article presents a comprehensive framework for implementing blockchain-based data integrity validation in autonomous vehicles. The proposed system addresses critical challenges in securing real-time sensor data through a hybrid architecture combining Hyperledger Fabric with Apache Kafka. By integrating distributed ledger technology with optimized data processing mechanisms, the system achieves both security and performance requirements essential for autonomous vehicle operations. The architecture incorporates smart contracts for data validation, multi-layered security protocols, and efficient data streaming capabilities. Results demonstrate that the proposed solution successfully balances the competing demands of data security and real-time processing, making it suitable for deployment in production autonomous vehicle environments.
Daria Smuseva, Andrea Marin, Sabina Rossi, Aad van Moorsel
A blockchain is an immutable ledger driven by a distributed consensus protocol. In public blockchains, such as Bitcoin and Ethereum Classic, consensus is established through a computational effort called Proof-of-Work (PoW). Special users called miners contribute to the PoW in exchange for a fee and also verify the data stored in blocks mined by the other miners. Here is where the Verifierās Dilemma emerges. Verification of blocks does not receive a reward, and to maximise their profits, miners may be incentivised to forego verifying blocks and to only invest their resources in PoW. In this article, we study the Verifierās Dilemma and a possible countermeasure consisting of the injection of invalid blocks using a quantitative model based on Markovian process algebra. To avoid the state space explosion problem, we study the underlying Markov chain by using a lumping that allows us to derive closed-form solutions for interesting performance indices. The analysis demonstrates the circumstances under which non-verifying miners gain fees higher than those of verifying miners. The model also allows us to derive the optimal rate at which invalid blocks must be injected so that skipping the verifying phase becomes economically disadvantageous whereas the throughput of the blockchain is only minimally reduced. The impact on minersā rewards and overall performance is also assessed.
This article examines key emerging technologies transforming financial platform engineering. Platform engineering plays a pivotal role in building these systems by leveraging microservices architecture, event-driven systems, and cloud-native technologies. This article explores how modern platform engineering practices ensure low latency, high throughput, security, and regulatory compliance while integrating cutting-edge technologies like machine learning and blockchain. Machine learning has revolutionized fraud detection by enabling the analysis of vast transactional datasets to identify patterns invisible to human observers. Blockchain technology has gained adoption for transaction verification, providing distributed ledger systems that ensure security and immutability while enabling smart contracts that automate complex financial agreements. Real-time analytics capabilities allow financial institutions to process streaming data for immediate insights on market trends, customer behavior, and risk factors, supporting data-driven decision-making at market speed. Finally, API ecosystems have created interconnected networks of services that facilitate innovation through standardized interfaces, transforming how financial services are developed and consumed across core banking, partner integration, and public marketplace contexts.
Soumya Narayana, B.H. Jaswanth Gowda, Umme Hani, Mohammed Gulzar Ahmed Ā· 6 authors
Hydrogels are innovative materials characterized by a water-swollen, crosslinked polymeric network capable of retaining substantial amounts of water while maintaining structural integrity. Their unique ability to swell or contract in response to environmental stimuli makes them integral to biomedical applications, including drug delivery, tissue engineering, and wound healing. Among these, "smart" hydrogels, sensitive to stimuli such as pH, temperature, and light, showcase reversible transitions between liquid and semi-solid states. Thermoresponsive hydrogels, exemplified by poly(N-isopropylacrylamide) (PNIPAM), are particularly notable for their sensitivity to temperature changes, transitioning near their lower critical solution temperature (LCST) of approximately 32 Ā°C in water. Structurally, PNIPAM-based hydrogels (PNIPAM-HYDs) are chemically versatile, allowing for modifications that enhance biocompatibility and functional adaptability. These properties enable their application in diverse therapeutic areas such as cancer therapy, phototherapy, wound healing, and tissue engineering. In this review, the unique properties and behavior of smart PNIPAM are explored, with an emphasis on diverse synthesis methods and a brief note on biocompatibility. Furthermore, the structural and functional modifications of PNIPAM-HYDs are detailed, along with their biomedical applications in cancer therapy, phototherapy, wound healing, tissue engineering, skin conditions, ocular diseases, etc. Various delivery routes and patents highlighting therapeutic advancements are also examined. Finally, the future prospects of PNIPAM-HYDs remain promising, with ongoing research focused on enhancing their stability, responsiveness, and clinical applicability. Their continued development is expected to revolutionize biomedical technologies, paving the way for more efficient and targeted therapeutic solutions.
In this article, the author analyzes the structure and mechanism of non-fungible tokens (NFT), in particular, the key stages of their use, benefits for creators and collectors, development prospects in this area and emerging problems. The main idea of the article is that at present, NFT is a revolutionary discovery in the field of art, contributing to the democratization of access to art and opening up new opportunities for monetization of digital content. The purpose of this study is to study the phenomenon of NFT as a new tool for realizing the creative potential of the author, and assess its impact on art. The main objective is to identify the main stages of the creation of non-fungible tokens, determine the features, advantages, disadvantages and legal aspects of this technology. When working on this study, the following methods were used: analytical, observation and comparison, systematization and synthesis. As a result of the study, it became clear that since 2017 there has been a steady increase in interest in the NFT sphere from users, and positive dynamics are expected in 2025-2026. The author outlined the current state and possibilities of NFT in the art market, revealed current problems and opportunities for authors, the mechanism of operation and advantages of this technology in the context of copyright, systematized possible NFT assets and ways of interacting with them, and considered measures to ensure user security to prevent hacker threats. Currently, NFT is a unique and promising mechanism that is continuously improving and is capable of significantly changing the perception of art and the ways people interact with art as digital assets.
This study discusses phishing detection on the Ethereum network using machine learning methods, specifically Graph Convolutional Networks (GCNs) and Enhanced Graph Attention Networks (EGAT). The background of this research is based on the increasing number of phishing attacks in the blockchain ecosystem that can threaten the financial security of users. The research aims to analyze the incidence rate of phishing attacks and develop effective and efficient detection methods. The methodology includes data collection from Ethereum transactions and phishing activities, followed by feature extraction, machine learning model training, and evaluation using metrics such as accuracy, precision, recall, and F-score. The identified research gap is the lack of focus on early-stage phishing detection in the Ethereum network and the suboptimal performance of existing methods in recognizing complex transaction patterns. The results indicate that EGAT achieves an accuracy of 93.6%, outperforming GCNs, which reach 91.2%. The conclusion of this research is that the EGAT method is superior in detecting phishing activities, providing significant contributions to security in the Ethereum network.
Property transactions in the UK are increasingly adopting blockchain technology to enhance efficiency, transparency, and security. However, the inherent transparency of blockchain raises significant data privacy risks and regulatory compliance challenges, particularly under the UK General Data Protection Regulation (UK GDPR). This study examines the role of Zero-Knowledge Proofs (ZKPs) in addressing these concerns by enabling transaction validation while preserving confidentiality. Using entropy measures, k-anonymity analysis, and logistic regression, this research quantitatively assesses the privacy risks, effectiveness of ZKPs, and regulatory acceptance in blockchain-based property transactions. The findings reveal that 65.5% of transactions remain highly or moderately identifiable, posing privacy vulnerabilities under UK data protection laws. ZKP-enabled transactions significantly enhance confidentiality, achieving a 92.5% transaction privacy score, compared to 48.3% for non-ZKP transactions. However, these privacy gains come at a 67.8% increase in transaction costs, highlighting a critical trade-off between security and efficiency. Regulatory approval rates for ZKP-based blockchain platforms stand at 72.5%, suggesting a strong potential for compliance advantages. While ZKPs improve privacy and regulatory alignment, challenges remain in terms of computational overhead, transaction costs, and adoption barriers. To facilitate large-scale implementation, this study recommends optimizing zk-Rollups for efficiency, developing clear policy frameworks, and enhancing collaboration between regulators, industry stakeholders, and blockchain developers. These steps are essential to ensuring a balance between privacy, scalability, and compliance, paving the way for secure and legally sound blockchain-based property transactions in the UK.
Lingli Qing, Ibrahim Alnafrah, Abd Alwahed Dagestani
The energy-intensive nature of cryptocurrency mining, largely reliant on fossil fuels in its early development, has raised growing environmental concern. Consequently, the Index of Cryptocurrency Environmental Attention (ICEA) has emerged, gauging public attention towards this issue. This study investigates the complex interplay between ICEA, cryptocurrency price and policy volatilities, green energy investments, and dirty energy prices. Utilizing a dataset spanning from January 2015 to June 2023, we employ a multifaceted approach encompassing cross-quantilogram, time-varying parameter vector autoregression (TVP-VAR), and wavelet coherence techniques to uncover the dynamic interconnectedness of these three markets. Our findings challenge a simplistic narrative that anticipates a direct link between ICEA and immediate reductions in electricity consumption within the cryptocurrency mining sector. Instead, we discern a nuanced picture wherein ICEA drives significant structural transformations, influencing investments in clean energy markets. Our analysis suggests that ICEA stimulates green energy investments, encouraging miners to explore alternative energy sources with lower environmental impacts . This transition paves the way for more sustainable investments , with green energy sources like renewables playing an increasingly prominent role in powering the cryptocurrency industry .
The advancement of Industrial Internet of Things (IIoT) has enabled cross-domain collaboration among enterprises, facilitating data exchange and coordinated operations for complex manufacturing tasks. As the primary security mechanism, cross-domain continuous authentication periodically verifies external devices to prevent unauthorized access and session hijacking, thereby mitigating system vulnerabilities. However, existing solutions face limitations: some rely on device-specific features incompatible with heterogeneous environments, while others neglect cross-domain scenarios, offering insufficient privacy protection and irreversible identity management. To address these gaps, we propose a cross-domain authentication framework leveraging zero-knowledge proofs and blockchain technology. Devices are assigned anonymous identities, with revocation managed via a distributed ledger. Initial authentication employs zero-knowledge proofs to generate valid tokens, while continuous authentication refreshes these tokens periodically. Security analysis confirms robustness against common threats, and performance evaluations demonstrate that periodic token renewal reduces computational and communication costs compared to repeated initial authentication processes.
The article is devoted to the study of the features of smart contracts, which are a type of electronic contracts. Smart contracts, which are also called āsmart contractsā (origin of the word āsmart contractā), correspond to modern trends in digitalization and provide an effective mechanism for the implementation of business, financial and economic relations in a virtual environment. The following methods were used in the study: general logical, method of analysis and synthesis, formal-legal, comparative-legal, systemic. When comparing the so-called ātechnologicalā and legal approaches to understanding the concept of āsmart contractā, the views of different groups of foreign and domestic scientists and researchers on the interpretation of this concept were analyzed. The principle of operation of a smart contract is considered on a specific example, while the way in which a smart contract operates in certain specific conditions is studied in detail and possible reasons for its failure to perform are analyzed. When analyzing the operation of smart contracts, their practical, technical, legislative problems and features were identified. Thus, the feature of immutability of a smart contract is its advantage because it excludes the intervention of the human factor. But the immutability of a smart contract is also its disadvantage because it makes it impossible to conclude additional agreements to a smart contract when certain circumstances change. Taking into account the study of the properties of a smart contract and an example of its operation, it can be stated that a smart contract can function only in a certain environment provided that the executable program code has direct and unlimited access to the objects of the smart contract. This creates integration problems of a smart contract with the objects of its operation. Thus, if the subject of a smart contract is real estate and in this regard the specified electronic contract requires notarial electronic certification and corresponding registration in the digital environment, then today in Ukraine there is an integration problem of electronic notarial certification of such contracts due to the absence and legislative uncertainty of the mechanism of electronic notarial certification and registration. Also relevant is the problem of smart contracts regarding payments under them in cryptocurrency, which also requires a legislative solution, since the legal status of cryptocurrency in Ukraine has not yet been established. Solving these problems in the future will allow for the wider use of smart contracts by their Ukrainian counterparties.
Blockchain technology is transforming industries like finance, supply chain, governance, and healthcare. This paper analyzes blockchain architecture, applications, challenges, and performance. Key attributesādecentralization, immutability, transparency, and securityāenable secure peer-to-peer transactions without intermediaries. Consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS) are examined for their trade-offs in scalability, energy efficiency, and security. In healthcare, blockchain addresses security and interoperability issues in centralized Personal Health Record (PHR) systems. Solutions using Ethereum, Hyperledger, smart contracts, and IPFS enhance Electronic Health Record (EHR) management by improving data integrity, privacy, and access control while reducing costs. A containerized microservices architecture further enhances scalability. Blockchain performance, evaluated using the BLOCKBENCH framework, highlights gaps in transaction throughput compared to traditional databases. Despite scalability, interoperability, and regulatory challenges, ongoing research focuses on optimizing consensus mechanisms, integrating database principles, and improving healthcare interoperability, advancing blockchainās real-world applications
Decentralized balloting using Ethereum blockchain is a cozy, obvious and tamper-proof manner of undertaking on line voting.Most existing E-Voting systems are based on centralized servers where the voters must trust the organizing authority for the integrity of the results. itās far a decentralized utility built on the Ethereum blockchain network, which allows contributors to solid their votes and look at the balloting effects with out the need for intermediaries.Blockchain is an immutable and indisputable public ledger. These ledgers exist in different locations, so any single failure does not affect the distributed ledger. In this gadget, votes are recorded on the blockchain, making it impossible for all people to control or regulate the outcomes. the usage of smart contracts guarantees that the vote casting technique is computerized, transparent, and comfortable. the usage of the blockchain generation and the implementation of a decentralized device provide a dependable and cost-powerful solution for undertaking honest and truth- ful elections.One essential democratic action is voting. Paper balloting, according to many experts, is the only suitable way to guarantee everyoneās right to vote. However, this approach is prone to misuse and mistakes. To overcome the challenges associated with paper voting, many countries use digital voting techniques. Massive vote-rigging could result from a single digital voting defect. Voting procedures for elections must be accurate, safe, convenient, and lawful. However, acceptability might be limited by problems with digital voting techniques. To solve these issues, blockchain technology was created because of its end-to-end verification capabilities. To ensure Blockchain technology has been utilized for voting in order to provide anonymity, privacy, verifiability, mobility, integrity, security, and fairness. Our suggested approach guarantees integrity, security, and anonymity by utilizing blockchain technology. This study also examines the difficulties blockchain electronic voting systems encounter and pinpoints areas that require further investigation to improve their reliability. Index TermsāBlockchain, Ethereum, Smart contracts, E- voting, Solidity, government, industry, security, survey, trans- parency.
Decentralized Finance (DeFi) is transforming the financial landscape by providing open, permissionless, and transparent access to financial services through blockchain technology and smart contracts.Unlike traditional financial systems, which rely on intermediaries such as banks and brokers, DeFi operates on decentralized networks, enabling peer-to-peer transactions and automated financial operations.This paper explores the key components of DeFi, including blockchain technology, smart contracts, liquidity pools, automated market makers (AMMs), decentralized exchanges (DEXs), stablecoins, and governance tokens.It highlights the benefits of DeFi, such as increased financial inclusion, lower costs, and improved transparency, while also addressing the associated risks, including smart contract vulnerabilities, market volatility, and regulatory challenges.The rapid evolution of DeFi, coupled with growing institutional interest and technological advancements, positions it as a transformative force in global finance.This paper concludes that despite ongoing challenges, DeFi has the potential to reshape the financial industry by decentralizing control and empowering users.
Identifying reputable Ethereum projects remains a critical challenge within the expanding blockchain ecosystem. The ability to distinguish between legitimate initiatives and potentially fraudulent schemes is non-trivial. This work presents a systematic approach that integrates multiple data sources with advanced analytics to evaluate credibility, transparency, and overall trustworthiness. The methodology applies machine learning techniques to analyse transaction histories on the Ethereum blockchain. The study classifies accounts based on a dataset comprising 2,179 entities linked to illicit activities and 3,977 associated with reputable projects. Using the LightGBM algorithm, the approach achieves an average accuracy of 0.984 and an average AUC of 0.999, validated through 10-fold cross-validation. Key influential factors include time differences between transactions and received_tnx. The proposed methodology provides a robust mechanism for identifying reputable Ethereum projects, fostering a more secure and transparent investment environment. By equipping stakeholders with data-driven insights, this research enables more informed decision-making, risk mitigation, and the promotion of legitimate blockchain initiatives. Furthermore, it lays the foundation for future advancements in trust assessment methodologies, contributing to the continued development and maturity of the Ethereum ecosystem.
Heike Joebges, Hansjƶrg Herr, Christian Kellermann
Abstract Crypto assetsā partial money-like use promotes toxic developments in the financial system. Even though crypto assets might be regarded as close substitutes to traditional money, we show that they lack important functions of money. Traditional fiat money requires several interacting institutions to stabilize its value and regulate its use. In our analysis, we elaborate on the risks associated with the difficulty of setting up regulatory institutions in the crypto sphere and the likelihood of periods of high volatility as well as their repercussions on the traditional financial system due to reciprocal integration. The shift of banking functions into the unregulated area of decentralized finance triggers a new quality of instability in the global financial system with an increasing probability of effects on the real economy. Regulation of crypto assets remains an urgent issue.
We present SmartShards: a new sharding algorithm for improving Byzantine tolerance and churn resistance in blockchains. Our algorithm places a peer in multiple shards to create an overlap. This simplifies cross-shard communication and shard membership management. We describe SmartShards, prove it correct and evaluate its performance. We propose several SmartShards extensions: defense against a slowly adaptive adversary, combining transactions into blocks, fortification against the join/leave attack.