Blockchain Papers

Shilpa Shree G R, Anupama Y K, Amutha S

No abstract is available for this record.

Evgeny Ukhanov

The proliferation of decentralized financial (DeFi) systems and smart contracts has underscored the critical need for software correctness. Bugs in such systems can lead to catastrophic financial losses. Formal verification offers a path to achieving mathematical certainty about software behavior. This paper presents the formal verification of the core logic for a token sale launchpad, implemented and proven correct using the Dafny programming language and verification system. We detail a compositional, bottom-up verification strategy, beginning with the proof of fundamental non-linear integer arithmetic properties, and building upon them to verify complex business logic, including asset conversion, time-based discounts, and capped-sale refund mechanics. The principal contributions are the formal proofs of critical safety and lifecycle properties. Most notably, we prove that refunds in a capped sale can never exceed the user's original deposit amount, and that the precision loss in round-trip financial calculations is strictly bounded. Furthermore, we verify the complete lifecycle logic, including user withdrawals under various sale mechanics and the correctness of post-sale token allocation, vesting, and claiming. This work serves as a comprehensive case study in applying rigorous verification techniques to build high-assurance financial software.

Quan Gu, Han Ye, Junjie Chen, Xiongfeng Ma

Quantum computers have the potential to break classical cryptographic systems by efficiently solving problems such as the elliptic curve discrete logarithm problem using Shor's algorithm. While resource estimates for factoring-based cryptanalysis are well established, comparable evaluations for Shor's elliptic curve algorithm under realistic architectural constraints remain limited. In this work, we propose a carry-lookahead quantum adder that achieves Toffoli depth $\log n + \log\log n + O(1)$ with only $O(n)$ ancillas, matching state-of-the-art performance in depth while avoiding the prohibitive $O(n\log n)$ space overhead of existing approaches. Importantly, our design is naturally compatible with the two-dimensional nearest-neighbor architectures and introduce only a constant-factor overhead. Further, we perform a comprehensive resource analysis of Shor's elliptic curve algorithm on two-dimensional lattices using the improved adder. By leveraging dynamic circuit techniques with mid-circuit measurements and classically controlled operations, our construction incorporates the windowed method, Montgomery representation, and quantum tables, and substantially reduces the overhead of long-range gates. For cryptographically relevant parameters, we provide precise resource estimates. In particular, breaking the NIST P-256 curve, which underlies most modern public-key infrastructures and the security of Bitcoin, requires about $4300$ logical qubits and logical Toffoli fidelity about $10^{-9}$. These results establish new benchmarks for efficient quantum arithmetic and provide concrete guidance toward the experimental realization of Shor's elliptic curve algorithm.

Yisong Chen, Chuqing Zhao, Yifan Gao

Introduction This systematic review comprehensively examines the application of blockchain in health insurance, highlighting the current state of research, inherent challenges, and future trends. Blockchains have demonstrated excellent potential in health insurance, especially in fraud prevention, claims processing, and data security. Moreover, this study also aims to identify several critical challenges that hinder their broader adoption and effectiveness, including data heterogeneity, individual task requirements, scalability and regulatory alignment. Methods System Review Results and Discussion Through comprehensive analysis, this study discusses some actionable solutions and strategies. Conclusively, this review underscores blockchain’s transformative impact on building a secure, efficient, and patient-centric health insurance system.

Edgar Roberto Dulce Villarreal, Julio Ariel Hurtado, Jose Garcia-Alonso, Enrique Moguel · 5 authors

Achieving a balance between interoperability and security in blockchain systems has led to the development of various integration mechanisms. These include the use of specialized smart contracts to facilitate cross-chain interactions, enabling reliable connections and secure transfers of information and assets. While technical interoperability is effectively addressed at lower layers, achieving semantic interoperability at the application layer remains a significant challenge. This paper proposes a mechanism to address this challenge by leveraging a model-driven approach. Metamodels, models, and transformations are created, and smart contracts are defined abstractly and then semi-automatically generated for specific blockchain platforms. The proposed approach was validated by generating contracts between Ethereum and Hyperledger, enabling semantically compatible transactions. The mechanism was further evaluated using the Technology Acceptance Model with expert participants. This evaluation demonstrated its effectiveness in specifying and transforming contracts and fostering semantic interoperability across blockchains.

Awad Duaibes

ABSTRACT Palestine's chronic energy insecurity, marked by high import dependency and structural fragmentation, poses major development challenges. In response, the Palestine Investment Fund (PIF) launched the Noor Palestine Solar Program, a public–private initiative aiming to install 200 Megawatts (MW) of solar capacity over 8 years, through utility parks and public‐school rooftops. This brief report draws on field‐based data to document the program's design, financing, and implementation. It highlights how the program mobilized concessional and private capital, navigated political and institutional constraints, and delivered measurable energy, fiscal, and educational outcomes. By late 2024, Noor had generated over 165 million kilowatt‐hours (kWh) of clean energy, saving nearly 70 million Israeli shekels (ILS) in imports. Key success factors included regulatory alignment, decentralized systems, blended finance, and flexible delivery. The program provides practical insights into how innovative energy infrastructure can be leveraged to strengthen service delivery and promote resilience and development in fragile settings.

Douglas L. L. Moura, Andre L. L. Aquino, Antonio A. F. Loureiro

The integration of multiple distributed ledgers in Intelligent Transportation Systems (ITS) introduces challenges for scalable and interoperable authentication. Traditional schemes, which rely heavily on Public Key Infrastructure (PKI), face limitations related to certificate management and key escrow. To address these issues, we propose a federated authentication system based on certificateless public key cryptography (CL-PKC) to enable seamless cross-domain and cross-chain authentication without relying on traditional certificates. The proposed approach is designed to operate at the edge, where authentication is performed close to the user to reduce latency and support mobility. Leveraging the CL-PKC scheme, each user independently generates and manages their own cryptographic keys. Simulation results show reduced credential generation time, lower network usage, and improved latency under heavy and cross-domain conditions.

E. Orestes O’Brien, Breno da Costa Paulo, Ángel Martín, Muhammad Shuaib Siddiqui · 5 authors

Future networks will deliver unprecedented performance, versatility, and efficiency, driven by advancements in automated monitoring and control. As networks evolve into interconnected platforms capable of enabling advanced features, allocating assets, and configuring them via northbound Application Programming Interfaces (APIs), dynamic control over multiple actors and stakeholders becomes essential. At this point, identity management plays a crucial role in overseeing onboarding, administering access, and registering activity to log and account for all operations. This paper compares the Open Common API Framework (CAPIF), based on the European Telecommunications Standards Institute (ETSI) standard, with a novel distributed identity-based approach using Distributed Ledger Technology (DLT). To assess the viability of these solutions, various tests are conducted to evaluate the frameworks’ latency and processing workloads.

Lorena Baigorria, Ana Gabriela Garis, Daniel Eduardo Riesco

Blockchain es la base tecnológica de una nueva forma de realiz-ar transacciones de manera segura en una red descentralizada. Dicha tecnología permite registrar la validez y el origen de los datos, y realizar transacciones de manera digital, compartida, inalterable y sin la intervención de intermediarios. Frecuentemente, las transacciones requieren de lógica automa-tizada. En estos casos, se vuelve necesaria la definición de con-tratos inteligentes, programas de computación almacenados en Blockchain que se ejecutan automáticamente cuando se cumplen condiciones predeterminadas. Los errores en contra-tos inteligentes pueden tener graves consecuencias, especial-mente en ámbitos como finanzas descentralizadas. Una clara definición de las condiciones es esencial; sin embargo, éstas son generalmente descriptas en lenguaje natural por las partes involucradas, lo que conlleva a la ambigüedad de interpretación por parte de los programadores del contrato. Por otro lado, los errores en la programación también pueden derivar a que el contrato no se ejecute como se esperaba. La calidad del contra-to inteligente podría ser mejorada si las condiciones fueran especificadas en UML con OCL, y luego transformadas al len-guaje de modelado Alloy para llevar a cabo la verificación y validación formal a través del método Model Checking. En este artículo, se describe una línea de investigación que propone un modelo para la especificación de contratos inteligentes en UML y OCL, complementado con una transformación automática a Alloy para su verificación y validación. Dicho modelo contribuye a realizar una auditoría más rigurosa de contratos inteligentes antes de despliegue en Blockchain.

Kaif Ali Khan Parigi, Kotaro Kataoka

Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLTs) are promising solution for IoT environments, offering scalability and high transaction throughput. Given the resource constraints of IoT Gateways (GWs), which maintain the ledgers, pruning of a ledger is important to prevent its size from increasing beyond the storage capacity of GWs. However, existing methods cannot simultaneously address the scalability and consistency issues for planning and executing the DAG based ledger pruning, consistency preservation, and orphaned transactions. We explore an approach that Storage Nodes (SNs) of the DAG based DLT plan the ledger pruning in an efficient, scalable, and consistent manner, and then GWs execute it. This paper introduces the Consensus based High Consistency Ledger Pruning (CHCLP) Framework, which uses two key techniques: Pruning List Reduction (PLR) and Consensus-based Pruning Mechanism (CPM). PLR aggressively compresses a long list of prunable transactions to the combination of a single transaction called "Adam Point" and the rest encoded as unique bit string paths from the Adam Point. CPM leverages Practical Byzantine Fault Tolerance consensus among SNs to ensure tamper-resistant agreement on the Pruning List (PL) and maintain DAG consistency across GWs. The CHCLP Framework was implemented by extending an existing benchmark DAG based DLT system. The proposed framework reduced the size of a PL by 98%, and the ratio of orphan transactions decreased to 0.5% compared to the benchmark system, which was 10.3%. The CHCLP Framework reduces the storage consumption of GWs in DAG based DLTs to a desirable extent with high consistency, and can drastically improve their scalability and performance.

Xiangyun Tang, Lidu Lou, Rui Peng, Tao Zhang · 9 authors

Vehicle Edge Computing (VEC) has emerged as a crucial element in modern vehicular computing systems, enhancing data processing efficiency between vehicles and nearby infrastructure, reducing latency, and improving the overall performance of intelligent transportation systems. However, VEC faces challenges, such as data inequality and privacy concerns, which may impede accurate data processing and decision-making across various components (e.g., vehicles, traffic signals, and roadside units). Existing studies attempt to address these challenges by relying on centralized servers to process cross-vehicle data. However, this approach introduces vulnerabilities, including single points of failure and potential performance bottlenecks. Moreover, many current methods overlook the need for data verifiability alongside privacy and security, thus complicating the traceability of data sources in vehicular environments. In this paper, we propose a verifiable, privacy-preserving cross-vehicle protocol based on relay chains, utilizing blockchain's distributed ledger technology to facilitate transparent and secure information sharing among vehicle edge nodes. Through tamper-proof bookkeeping and automated smart contracts, the protocol significantly enhances the efficiency and security of VEC. The relay chain functions as the central framework, employing homomorphic encryption and distributed private key technology to enable confidential data sharing and verifiable access to business-critical information across nodes. This solution effectively tackles the pressing challenges of privacy protection, reliability, and data traceability within current VEC systems. To enhance practicality, the protocol adopts a non-iterative and lightweight design, enabling efficient data exchange and low-latency cross-chain interaction in heterogeneous VEC systems. We demonstrate the feasibility and effectiveness of our protocol through extensive experimental data supported by theoretical analysis. The results show that the proposed protocol achieves competitive performance in computation cost, encryption latency, and cross-chain throughput, especially under increasing key sizes and node densities, confirming its efficiency and scalability in real-world vehicular deployments.

Javier Godoy, E. López Torres, Juan Pablo Galeotti, Diego Garbervetsky · 5 authors

No abstract is available for this record.

Ahmad A Alsharidah, Devki Nandan Jha, Ellis Solaiman, Bo Wei · 6 authors

Federated learning is a promising approach that enables collaborative machine learning (ML) in distributed environments, such as the Internet of Medical Things (IoMT) while preserving consumer privacy. It allows multiple consumers to collaboratively train a model using their own data, sharing only the locally trained model rather than the raw data. Most existing federated learning systems assume a high level of trust in participating nodes, which is unrealistic in real-world consumer-centric scenarios. Involving untrusted nodes can compromise the integrity of the training process and result in potential data breaches. To address these challenges, this paper presents REWARDCHAIN, a novel federated learning framework that leverages blockchain technology to ensure trust and accountability among untrusted IoMT consumers. By recording all model updates and client contributions on an immutable blockchain ledger, REWARDCHAIN allows auditing of the entire training process and attributing any malicious behaviour to specific nodes. Moreover, we design an incentive mechanism that evaluates contributions based on data quality and participant reputation. This system motivates participants to contribute high-quality data through a reputation-constrained reward allocation. Our evaluations show that REWARDCHAIN effectively balances trust, security, and model performance, facilitating a more secure and effective federated learning ecosystem.

Soubhagya Ranjan Mallick, Veena Goswami, Rakesh Kumar Lenka, Rabindra K. Barik · 6 authors

A digital revolution is taking place in healthcare due to rising patient data volumes, concerns about privacy and security, and the need for interoperable solutions. The demand for trustworthy, scalable, and interoperable technologies has become essential in this fast-growing healthcare industry. Conventional centralised systems regularly encounter challenges meeting these requirements because of problems including storage structure, data privacy, security vulnerabilities, network complexity, and lack of scalability. Additionally, current blockchain implementations frequently face challenges with interoperability, trust management among several healthcare stakeholders, and throughput bottlenecks. To overcome these challenges, this paper introduces a novel framework called LIVER: a Lightweight Infrastructure for Verifiable Electronic Records that integrates Blockchain, InterPlanetary File System (IPFS), Edge computing, and Internet of Medical Things (IoMT) to address these issues. Distributed processing based on edge computing and IPFS, cryptographic methods, blockchain consensus mechanisms, and an immutable ledger allows it to be scalable, secure, interoperable, and boast tamper-proof data integrity. Furthermore, a unique queueing approach has been implemented to improve operational efficiency, which controls patient flow, decreases wait times, maximises resource utilisation, minimises healthcare delays, and enhances the patient experience. Finally, based on the experimental evaluation results, the LIVER framework reduces ledger size, facilitates enhanced data sharing, and improves the healthcare system’s efficiency, scalability, security, and performance. The goal is to provide a framework that can handle the computational and operational limitations of existing healthcare systems while still protecting patient privacy and allowing for scalability.

Allan Edgard Silva Freitas

Quantum computing threatens foundational cryptographic assumptions in today’s distributed ledgers, while application demands outgrow the throughput and latency ceilings of single-chain blockchains. Directed acyclic graph (DAG) ledgers unlock parallelism but raise new questions about ordering, security, and light-client viability. This position paper argues for a postquantum (PQ) DAG ledger that matches DAG concurrency with PQ-secure consensus and transactions, plus a privacy-preserving identity/reputation layer. We sketch the architecture, situate it against the literature, and enumerate some open challenges to be addressed for deployment at scale. A carefully engineered PQ DAG can provide credible security and performance in a quantum-enabled adversarial landscape.

Jeyakumar Samantha Tharani, E.Y.A. Charles, Punit Rathore, Zhé Hóu · 6 authors

Blockchain is a distributed ledger technology that provides pseudo-anonymity among participants to maintain privacy. However, malicious actors utilise this property to hide their illegal rewards received through cyber attacks, dark market trades, money laundering and Ponzi schemes. The recent confiscation by the FBI of more than $4 million USD worth of bitcoin from the ‘Silk Road’ dark marketplace indicates the scale of the problem faced by financial regulators and law enforcement authorities. Analysing and identifying harmful actors is, therefore, necessary to regulate the transactions of digital assets. Machine learning models can assist in detecting patterns and correlations between the actors in blockchain networks that may not be apparent through traditional methods. In blockchain networks, the number of actors linked to illegal activities is significantly smaller than that of regular activities. Also, only very limited labelled transaction data is available about these malicious actors. These limitations make it harder to train supervised learning models to provide real-time proactive responses. This article represents a pioneering effort in thoroughly examining the different unsupervised learning methods for clustering suspicious behaviour of actors within blockchain networks. The proposed unsupervised learning-based analysis considers metadata and interconnectivity information of blockchain transactions. The metadata contains time-based and amount-based information. Interconnectivity data represents centrality measures and embedding vectors of the blockchain network. The quality of the identified clusters is validated using internal and external cluster validation measures. The validation results were used to identify influential features using the eXplainable AI technique Shapley (ShAP) values. The results reveal that the features related to the spending and receiving transactions strongly influenced cluster identification. Overall, the centroid-based and connectivity-based approaches identified well-separated clusters for metadata and centrality-based features of blockchain transactions.

Carlos Cardoso, Caio Silva, Alan Veloso, Jeffson Sousa · 5 authors

As Distributed Ledger Technologies (DLTs) mature into production-grade systems, a critical gap emerges between protocol-level benchmarking and application-centric performance testing. While specialized tools like Hyperledger Caliper excel at measuring core on-chain metrics, they are less suited for evaluating the end-to-end performance of applications that interact with the DLT through an intermediary API layer. This paper addresses this gap by proposing a three-tier, API-driven framework that enables mature, general-purpose load testing tools, such as Apache JMeter, to realistically assess a Hyperledger Besu network’s performance from an application’s perspective. The core of our solution is a custom API server that provides essential services like atomic nonce management and dynamic load balancing. Our comparative analysis demonstrates that while Caliper may report higher end-to-end throughput under specific conditions, our framework induces a significantly more substantial and evenly distributed load, revealing a more accurate picture of the network’s true processing capacity. Furthermore, our approach captures API-layer latency—a crucial metric for client-perceived responsiveness—which proved to be an order of magnitude lower than the on-chain finality measured by Caliper. This work validates a reusable architectural pattern for testing DLTs within a realistic application stack, bridging the gap between protocol benchmarking and real-world performance engineering.

Evan W. Wu, Marius Jurt, Yichao Jin

The proliferation of multi-vendor autonomous systems (MVAS), such as shared warehouses, necessitates robust cooperation frameworks for robotic agents from different vendors. Ensuring operational integrity in these environments is a critical challenge, as the misbehaviour of a single agent can disrupt the entire system. This paper proposes a decentralised framework for secure and trustworthy multi-robot cooperation. Our approach leverages distributed ledger technology (DLT) to create an immutable record of operations and introduces a novel, lightweight Proof of Location (PoL) mechanism. This PoL allows agents to verify task completions both physically and cryptographically with minimal computational overhead. The framework is further strengthened by a real-time, algorithmic trust and reputation system that continuously evaluates agent behaviour. A key advantage over traditional methods is our support for asynchronous verification, which enhances both scalability and efficiency by removing centralised bottlenecks. Extensive simulations in a warehouse setting demonstrate that our framework effectively detects and mitigates malicious activities, thereby improving the security and performance of MVAS. The broader applicability of our approach is further illustrated through a conceptual case study in a smart city parking scenario.

Yair Rivera Julio, Ángel D. Pinto Mangones, Nelson A. Pérez-García, Mónica-Karel Huerta · 9 authors

Large-Language-Model (LLM) functionality is rapidly becoming a cornerstone of Telemedicine-as-a-Service (PGaaS) platforms. Recent Q1 studies demonstrate that even minuscule training-set or parameter perturbations can introduce persistent back-doors, while inference pipelines leak protected health information (PHI) if left unguarded. Building on the NIST AI Risk Management Framework (AI RMF), this paper proposes and implements a zero-trust, multi-cloud security architecture that couples (i) knowledge-graph–driven data-integrity validation, (ii) containerised fine-tuning isolation, (iii) AI-RMF–centred governance and continuous risk registers, (iv) a privacy-preserving response-sanitisation gateway enhanced with one-time-password (OTP) and KYC identity binding, and (v) remote-attestation-backed zero-knowledge-proof (ZKP) integrity challenges for model weights at runtime. An extensive multi-cloud evaluation shows that the framework detects 94.6 % of tainted samples before ingestion and blocks 91.3 % of unsafe outputs, with a median latency overhead of 66 ms—well below clinical tele-consultation thresholds.

Hooda, Shakti

This dissertation analyzes how the European Union (EU) is able to regulate crypto-assets with the proposed Regulation on Markets in Crypto-Assets (MiCA). Crypto-assets havebeen regarded as one of the most disruptive advancements in finance and have beenableto operate without the use of traditional intermediaries and are able to challenge thecurrent regulatory frameworks. Besides the opportunities these crypto-assets bring for thefinancial sector, there is also the concern of financial stability, consumer protection, andintegrity of the market. These aspects also need to be considered with the use of innovative technologies. The approach to this research is both doctrinal as well as comparative. The research first describes the foundational concepts and technologies of crypto-assets and decentralizedfinance (DeFi) along with stablecoins and non-fungible tokens (NFTs). Afterwards theMiCA proposal is described in a certain detail. This is particularly in relation totheoverall EU financial regulation and its fulfillment to custody, disclosure, governance andlicensing aspects. To assess the extent of which MiCA is adequate, this dissertation reviews the pragmatics of the EU miCA with that of other major jurisdictions, like the US, the UK, andtheframeworks constructed by global organizations like the Financial Stability Board or theFinancial Action Task Force. Such a comparative analysis underscores a lack of a unifiedlegal framework especially with respect to DeFi, NFTs, and cross-border jurisdictional issues. The dissertation finds that MiCA is an integral building block towards the convergence of crypto-asset legislation in the EU. It decreases the confusion and discordant regulatorylandscape. However, it also maintains that MiCA is overlooking important elements likethe control of decentralized systems and the enforcement of anti-money launderinglegislation. Enhanced international collaboration and regulatory amendments will benecessary in order to foster the innovative frameworks that will ensure the stability of the financial systems.

Jaibir Singh, Salil Bharany, Suman Rani, Ateeq Ur Rehman · 7 authors

The convergence of blockchain, artificial intelligence (AI), and cloud computing is catalyzing a paradigm shift in developing secure, intelligent, and scalable digital infrastructures. This triad of technologies is increasingly utilized to improve performance, transparency, and trust in engineering-driven and socio-technical environments. This study systematically reviews the evolution, integration strategies, and applications of blockchain, AI, and cloud computing in digital ecosystems. The analysis is based on 108 peer-reviewed studies spanning the years 2012 to 2025. A comprehensive literature analysis was conducted to identify trends, synergies, and sector-specific implementations of these systems. The review explores how their integration supports real-world engineering and operational use cases. Blockchain contributes to decentralized architectures, secure data exchange, and identity verification. AI supports adaptive behavior, autonomous decision-making, and predictive analytics. Cloud computing offers the scalable infrastructure necessary for deployment. Key challenges addressed include interoperability, latency, security trade-offs, and resource allocation. Use cases in digital finance, supply chain management, and industrial automation demonstrate the effectiveness of this integration in building resilient, ethically aligned, and high-performance infrastructures. The findings offer valuable insights and technical considerations for engineers and architects seeking to design next-generation cyber-physical systems that are secure, intelligent, and socially responsive. Clinical Trial Number Not applicable.

Vidiasha Beejan, Girish Bekaroo

No abstract is available for this record.

Vitor Emanuel Batista, Guilherme Koslovski, Maurício A. Pillon, Charles C. Miers · 6 authors

Cloud computing has become the dominant choice for hosting various systems and services, with substantial public cloud service spending growth. This trend has extended to blockchain technology, which offers decentralized solutions for diverse applications. Concurrently, there is an increasing focus on business models incorporating Environmental, Social and Governance (ESG) aspects. One such initiative is Carbono21, a platform generating tokens in response to reforestation actions and the carbon credit market. In this context, this article examines the performance aspects of generating Non-Fungible Tokens (NFTs) in a blockchain environment under stress conditions. The Hyperledger Caliper was the benchmark tool used in experiments conducted to analyze the blockchain’s resilience and stability. Linear regression models showed a strong positive correlation between memory usage and total transactions. These results highlight the need for precise resource sizing and robust monitoring mechanisms to prevent service degradation under high transaction loads.

Sajarupan Tharumaraja, Madura Prabhani Pitigala Liyanage, Akila Wijethunge, Janaka Ekanayake

The integration of Distributed Energy Resources (DERs), such as rooftop photovoltaic (PV) systems and Battery Energy Storage Systems (BESS), enables peer-to-peer (P2P) energy trading in microgrids, enhancing grid flexibility and optimizing operational management. This study presents an automated, blockchain-enabled framework for very short-term (VST) P2P trading, tested using Sri Lanka's tariff data to harness the economic and operational potential of decentralized energy systems. The Intelligent Prosumer Energy Node (IPEN) facilitates autonomous energy trading through real-time monitoring, VST demand forecasting, recommendations from the OpenDSS Demand-Side Management (O-DSM), and userguided decisions. Similarly, the Intelligent Consumer Energy Node (ICEN) autonomously executes trading based on power demand monitoring, forecasting, and O-DSM guidance. The blockchain network, built on Hyperledger Fabric, secures and transparently manages transactions across five organizations, supported by multiple channels and smart contracts. Three trading models, Feed-in Tariff (FiT), P2P without storage, and P2P with BESS, were evaluated across prosumer-to-consumer ratios of$25:75,50:50$, and$75:25$. Results show that automated P2P trading outperforms FiT, with BESS providing the highest economic gains. Prosumers achieved up to 35.1% higher profits, while consumers reduced costs by up to 15.2%, demonstrating the system's potential for scalable microgrid deployment.