Blockchain Papers

Komal Mishra

No abstract is available for this record.

A. Brahmareddy, Arun Kumar Arigela, Dr. Mercy Paul Selvan, T. S. Sreenivas · 6 authors

No abstract is available for this record.

Wencheng Chen, Jun Wang, Jeng-Shyang Pan, R. Simon Sherratt · 5 authors

The rapid advancement of Industry 5.0 has accelerated the adoption of the Industrial Internet of Things (IIoT). However, challenges such as data privacy breaches, malicious attacks, and the absence of trustworthy mechanisms continue to hinder its secure and efficient operation. To overcome these issues, this paper proposes an enhanced blockchain-based data storage framework and systematically improves the Delegated Proof of Stake (DPoS) consensus mechanism. A four-party evolutionary game model is developed, involving agent nodes, voting nodes, malicious nodes, and supervisory nodes, to comprehensively analyze the dynamic effects of key factors—including bribery intensity, malicious costs, supervision, and reputation mechanisms—on system stability. Furthermore, novel incentive and punishment strategies are introduced to foster node collaboration and suppress malicious behaviors. The simulation results show that the improved DPoS mechanism achieves significant enhancements across multiple performance dimensions. Under high-load conditions, the system increases transaction throughput by approximately 5%, reduces consensus latency, and maintains stable operation even as the network scale expands. In adversarial scenarios, the double-spending attack success rate decreases to about 2.6%, indicating strengthened security resilience. In addition, the convergence of strategy evolution is notably accelerated, enabling the system to reach cooperative and stable states more efficiently. These results demonstrate that the proposed mechanism effectively improves the efficiency, security, and dynamic stability of IIoT data storage systems, providing strong support for reliable operation in complex industrial environments.

Arda Hacıfevzioğlu, Kübra Kalkan

No abstract is available for this record.

Tony Evans Adisurya

In recent years, the rapid growth of Decentralised Finance (DeFi) has revolutionised traditional financial services, with approximately $120 billion in total value locked (TVL) across various protocols. However, this expansion has been accompanied by significant security challenges, including major losses from DeFi hacks alone. The absence of centralised safety nets and the technical complexity of smart contract auditing have created substantial barriers to mainstream DeFi adoption, particularly among risk- averse users who lack the expertise to assess protocol vulnerabilities independently. This report presents the design and implementation of a decentralised insurance protocol that addresses these critical risk management challenges through an innovative tokenisation model. The proposed system introduces Insurance Tokens (ITs) and Principal Tokens (PTs) as the core mechanisms for providing insurance coverage against smart contract exploits and protocol failures in DeFi. ITs represent units of insurance coverage that can be freely traded on decentralised exchanges (DEXs) until expiration, enabling a liquid secondary market for DeFi insurance. PTs represent ownership stakes in the coverage fund, allowing underwriters to provide capital while maintaining the flexibility to exit positions through token sales or redemption at maturity. The protocol hopes to create a more accessible DeFi ecosystem by providing transparent, efficient and accessible insurance coverage, ultimately contributing to broader DeFi adoption and establishing a trustworthy framework for on-chain risk management.

Hojung Lim, Dong-Myung Shin

No abstract is available for this record.

Abdullah Ayub Khan, Asif Ali Laghari, Hamad Almansour, Teerath Kumar · 7 authors

Wearable health technology has revolutionized remote monitoring and personalized healthcare by allowing real-time surveillance of patient health measurements and vital signs. However, their widespread acceptance is hampered by issues with security, privacy preservation, data protection, and interoperability. Blockchain Technology (BT), in particular Zero-Knowledge Proofs (ZKPs) and smart contracts, present a viable way to enhance the privacy, provenance, and integrity of wearable health data. This paper proposes a BT-enabled system that guarantees decentralized, unforged data management, transparency, immutability, and dynamic traceability for wearable health devices, particularly smartwatches with biosensors. To evaluate the effectiveness of the proposed work, the main performance-related metrics-latency, throughput, computational overhead, security robustness, and scalability-are looked at. The experiment's simulated findings show that BT integration is effective, with a 99.33% improvement in data integrity and protection. Automated access control protocols demonstrate data protection by utilizing smart contracts, and ZKPs guarantee verifiable data exchanges without jeopardizing patient privacy. These results demonstrate improved interoperability, decreased processing time, and increased security in comparison to comparable cutting-edge centralized platforms.

Aarti Punia, Preeti Gulia, Nasib Singh Gill, Deepak Kaushik · 7 authors

An effective healthcare data system must safeguard individual privacy, foster public trust, and enhance societal resilience. To achieve this, access to critical health information must be provided in an ethical, secure, and reliable manner. This paper proposes a blockchain-based healthcare management framework designed to improve security, privacy, and transparency in healthcare administration. The architecture incorporates smart contracts, multi-signature wallets, and zero-knowledge proofs (ZKPs) to securely facilitate key operations such as patient registration, policy updates, and medical device management on a decentralized platform. Multi-signature wallets require authorization from multiple stakeholders for sensitive transactions, while ZKPs enable identity or access verification without disclosing confidential information. A built-in performance monitoring module collects key metrics, including transaction latency, gas consumption, and block time, which are visualized using JavaScript. Overall, the proposed system offers a secure, transparent, and privacy-preserving approach to decentralized healthcare management.

Ana Julia Evangelista Andrade, Flavio Cezar Amate

This paper presents the design, implementation, and evaluation of a decentralized system for issuing and verifying academic certificates based on blockchain technology. The proposed solution addresses common limitations of traditional certification models, such as susceptibility to forgery, reliance on centralized infrastructures, and inefficient verification processes. The system is built on the TRON blockchain and integrates smart contracts written in Solidity, a decentralized web application (dApp) for user interaction, and the InterPlanetary File System (IPFS) for decentralized storage of certificate metadata. The methodology comprised architectural design, smart contract development, and the implementation of a web-based interface, followed by functional, security, performance, and usability evaluations. Experimental results show that the system correctly supports certificate issuance and public verification, enforces access control, and resists common misuse scenarios. Performance analysis indicates low confirmation latency and negligible transaction costs, making the solution suitable for large-scale academic environments. Additionally, usability assessment using the System Usability Scale (SUS) resulted in a score of 76.67, indicating good user acceptance. Overall, the results demonstrate the technical feasibility and practical viability of the proposed approach, highlighting the TRON blockchain as an effective and cost-efficient infrastructure for decentralized academic certification systems.

Jiho Lee, Jieun Lee, Zehua Wang, JaeSeung Song

The proliferation of Internet of Things (IoT) applications in safety-critical domains, such as healthcare, smart transportation, and industrial automation, demands robust solutions for data integrity, traceability, and security that surpass the capabilities of centralized databases. This paper analyzes how blockchain technology can be integrated with core IoT service functions—including data management, security, device management, group coordination, and automated billing—to enhance immutability, trust, and operational efficiency. Our analysis identifies practical use cases such as consensus-driven tamper-proof storage, role-based access control, firmware integrity verification, and automated micropayments. These use cases showcase blockchain’s potential beyond traditional data storage. Building on this, we propose a novel framework that integrates a permissioned distributed ledger with a standardized IoT service layer platform through a Blockchain Interworking Proxy Entity (BlockIPE). This proxy dynamically maps IoT service functions to smart contracts, enabling flexible data routing to conventional databases or blockchains based on the application requirements. We implement a Dockerized prototype that integrates a C-based oneM2M platform with an Ethereum-compatible permissioned ledger (implemented using Hyperledger Besu) via BlockIPE, incorporating security features such as role-based access control. For performance evaluation, we use Ganache to isolate proxy-level overhead and scalability. At the proxy level, the blockchain-integrated path achieves processing latencies (≈86 ms) comparable to, and slightly faster than, the traditional database path. Although the end-to-end latency is inherently governed by on-chain confirmation (≈0.586–1.086 s), the scalability remains high (up to 100,000 TPS). This validates that the architecture secures IoT ecosystems with manageable operational overhead.

Adnan Imeri, Uwe Roth, Michail Alexandros Kourtis, Andreas Oikonomakis · 10 authors

Reliable data availability and transparent governance are fundamental requirements for distributed edge-to-cloud systems that must operate across multiple administrative domains. Conventional cloud-centric architectures centralize control and storage, creating bottlenecks and limiting autonomous collaboration at the network edge. This paper introduces a decentralized governance and service-management framework that leverages Decentralized Autonomous Organizations (DAOs) and Decentralized Applications (DApps) to to govern and orchestrate verifiable, tamper-resistant, and continuously accessible data exchange between heterogeneous edge and cloud components. By embedding blockchain-based smart contracts within swarm-enabled edge infrastructures, the approach enables automated decision-making, auditable coordination, and fault-tolerant data sharing without relying on trusted intermediaries. The proposed OASEES framework demonstrates how DAO-driven orchestration can enhance data availability and accountability in real-world scenarios, including energy grid balancing, structural safety monitoring, and predictive maintenance of wind turbines. Results highlight that decentralized governance mechanisms enhance transparency, resilience, and trust, offering a scalable foundation for next-generation edge-to-cloud data ecosystems.

Fengfeng Bai, Kai Liu, Jihua Liu

The suggested paper introduces an improved lightweight blockchain model designed for smart city infrastructures, mainly focused on intelligent IoT scenarios. Today, smart cities mainly depend on interconnected IoT devices to improve services like transportation, energy and public safety. However, blockchain systems face significant difficulties due to high processing demands, data duplication and capacity problems. To address these issues, in this study, we proposed a novel model called Adaptive Hybrid Consensus (AHC), which combines the advantages of consortium and consensus lightweight concepts. Using a role-based hierarchy, this system classifies IoT devices according to their computing and storage abilities. Here, high-capacity nodes such as fog and edge computing devices can handle data validation and temporary storage, whereas low-capacity IoT devices focus on pre-validating data using an Assisted Local Consensus (ALC) method. Proof of Adaptive Authority and Stake (PoA-S) is a lightweight consensus technique that helps to continuously select validators according to their interest, workload and credibility to ensure balanced and effective operations. By storing only the important data on the blockchain and distributing non-essential data to edge nodes, the Assisted Selected Relevant Data in Local Ledger (ASRDLL) technique is used. Also, it helps to create a selective data storage strategy and reduces storage overhead. Topic-based partitioning is performed further to improve the network performance by classifying data according to their respective application domains. Then, the system enhances network performance by grouping data based on specific areas like healthcare and traffic management. It also focuses on quickly handling essential and time-sensitive data to ensure fast responses in serious situations. This design was tested using a prototype regarding energy reduction efficiency, data handling efficiency and quick response compared to the existing blockchain approaches. Therefore, again, this approach proves its efficacy in resource-constrained IoT environments and makes it suitable for smart cities.

Abdullah Aljumah, Tariq Ahamed Ahanger, Imdad Ullah

Unmanned Aerial Vehicles (UAVs) are increasingly deployed across diverse domains such as surveillance, logistics, and disaster management. However, ensuring the safety, security, and trustworthiness of UAV operations remains a significant challenge, primarily due to vulnerabilities in centralized data processing architectures. Traditional UAV systems rely on remote cloud servers to perform machine learning (ML)-based analytics, which introduces issues such as data exposure, latency, scalability bottlenecks, and susceptibility to cyberattacks during data transmission and storage. These challenges underscore the urgent need for a decentralized, verifiable, and privacy-preser ving learning mechanism that can support collaborative UAV intelligence without centralized control. To address these limitations, this study proposes a blockchain-enabled distributed ML framework that facilitates secure, peer-to-peer collaboration among UAV nodes. The framework integrates blockchain’s immutable ledger and smart contracts with decentralized ML models, enabling UAVs to share and validate trained models rather than raw data. This ensures data confidentiality, integrity, and transparency throughout the learning process. A stacking-based ensemble mechanism is employed to enhance predictive performance through collaborative knowledge aggregation. The proposed system is experimentally validated using a collaborative intrusion detection (ID) scenario using the KDD99 network attack data set and real-world implementation. The results demonstrate significant improvements in detection accuracy, latency and F1-score compared to conventional centralized ML methods, achieving an average accuracy of 97.9%, latency 198ms, and F1-score exceeding 97%. These outcomes confirm that the integration of blockchain and decentralized ML effectively mitigates cybersecurity risks while enabling scalable, trustworthy UAV intelligence.

Giovana Milenka Ciprián Herrera

This deliverable describes the technical foundations and integration approach of the EU‑DREAM Data Management Platform, developed under Task 3.4 between M4 and M18. The platform acts as the central layer enabling secure, consistent, and reliable data exchange across the EU‑DREAM ecosystem, connecting components such as the Data Platform, Digital Twins, Distributed Ledger Technology, NLP‑based intermediator, and other energy applications. It defines the overall architecture in line with industry best practices, European recommendations, and earlier system designs, while detailing the operation of key components including identity and access management, API gateways, and DevOps‑based deployment environments. The deliverable also introduces a reference infrastructure to support integration with external systems such as sensors, energy management systems, IoT devices, external databases, and Living Labs. Designed to be modular, scalable, and replicable, the platform allows components to evolve independently while enabling consistent deployment across multiple locations and use cases.

Swati Gupta, Dinesh Chandra Misra

As the healthcare systems become more digital, a problem of data security, patient information safety, and the methods of guaranteeing that the information is available to everyone has come to the fore. Role-Based Access Control (RBAC) and other crude mechanisms of determining who is allowed to access what data are limited in preventing breaches and unlawful manipulation of data. To address these issues, this paper will propose the use of blockchain-based technology to develop a smart contract architecture that would enhance the process of managing healthcare data in a more transparent and secure way. The solution offered is based on the programmable smart contracts and the blockchain technology that cannot be altered and is decentralized to ensure that audits can be performed, data integrity is ensured, and access control is configured. According to simulated deployment studies, the proposed plan is much better than the current designs in the deterrence of unauthorized access, reduction of data modification and reducing the cost of operation.

Nayana More, Sandeep Vanjale, Gauri R. Rao, Madhavi Mane

This study introduces a blockchain-based framework designed to strengthen the privacy, security, and verifiability of Electronic Health Records (EHRs) within Internet of Things (IoT)-driven healthcare environments. The proposed hybrid model combines blockchain for tamper-proof data logging, the InterPlanetary File System (IPFS) for scalable and efficient off-chain storage, and advanced cryptographic mechanisms such as smart contracts and Zero-Knowledge Proofs (ZKPs) to enable secure access management. Within this architecture, patients retain ownership and control of their encrypted medical data, while healthcare providers obtain permissioned access verified through ZKP-enabled smart contracts. Comparative evaluation reveals notable performance gains—92% enhancement in data integrity, 87% improvement in privacy protection, and a 30–35% reduction in unauthorized access—relative to conventional centralized EHR systems. Additionally, the framework demonstrates over 40% higher auditability and trust among healthcare entities. Remaining research challenges include achieving cross-platform interoperability, ensuring regulatory compliance, and integrating advanced privacy-preserving technologies such as federated learning and homomorphic encryption. Future work aims to optimize consensus mechanisms and align the framework with HL7 FHIR standards to facilitate scalability and real-world deployment.

Dawood Alalisalem, Hafizur Rahman

Recently, it has been noted that the convergence of blockchain technology presents a promising paradigm for secure, privacy-preserving, and transparent healthcare systems. Moreover, Digital Twins enable real-time replication of patients, hospital operations, and medical devices, and their dependence on continuous sensitive data streams introduces the latest trust and Cybersecurity challenges. A systematic literature review aims to investigate how distributed ledger and blockchain technologies have been applied to secure healthcare digital twins from 2020 to 2025. Furthermore, the review addresses the proposed architecture of blockchain, the security objectives targeted, integration approaches within digital twins, and evaluation methods with limitations. The study follows PRISMA 2020 guidelines. Web of Sciences, IEEE Xplore, PubMed, Scopus, and ACM Digital Library were searched from January 2020 to October 2025 by using defined Boolean queries. Also, the focus of the inclusion criteria is on peer-reviewed studies that discussed blockchain for DT security in healthcare. Data extraction captured blockchain type, metadata, security mechanisms, DT domain, and evaluation methods. From the 487 identified records, only 20 successfully met the inclusion criteria. The fact behind it is that most studies only employed permissioned blockchains like Quorum and Hyperledger integrated with digital twins for monitoring patients, device lifecycle tracking, and data provenance. Some main security objectives include provenance assurance, access control, and integrity. Moreover, only some studies provide formal threat analysis or real-world deployment. Blockchain technology is reliable because it increases digital twin security through immutability, smart-contract-based governance, and decentralized trust. However, interoperability, scalability, and privacy-preserving computation remain the main barriers for clinical adoption.

Shiva Soni, Abhilasha Singh

The rapid growth of IoT devices in smart home environments has introduced significant challenges in ensuring secure, scalable, and efficient communication among heterogeneous devices. Centralized architectures suffer from a single point of failure, while blockchain-only solutions face high latency, limiting their use in real-time control. To address these issues, we propose a multi-layered decentralized framework that combines a consortium blockchain, a trusted off-chain coordinator, group-based zero-knowledge proofs (ZKPs), and a two-tiered access control policy (ACP) architecture. The consortium blockchain provides an immutable ledger for device identities and foundational, coarse-grained ACP enforcement through smart contracts, ensuring tamper-proof trust. For privacy-preserving mutual authentication, a group-based ZKP protocol enables collective device authorization without revealing sensitive keys. The off-chain coordinator complements this by enforcing dynamic security mechanisms, including fine-grained ACPv2 checks—such as rate limits, time-of-day restrictions, and device telemetry—in addition to anomaly detection for behavioral risk assessment. This proposed hybrid structure achieves both immutability and high efficiency over traditional methods. A performance evaluation highlighted the framework’s efficiency by demonstrating that the core ZKP verification for a 500-device group can be completed in just 190 ms. The framework drastically reduces on-chain costs, with critical access control policy transactions consuming only 82,748 gas—a reduction of over 90% compared to benchmarked on-chain systems. The complete end-to-end workflow, from user request to secure session establishment, has a latency bound of approximately 3s. Formal security verification with the BAN and AVISPA tools validates resilience against common attacks, including man-in-the-middle, replay, and impersonation, while static analysis using the Slither framework confirms the absence of critical vulnerabilities in the smart contract code. By combining an immutable on-chain foundation with intelligent, dynamic off-chain enforcement, our proposed framework provides a uniquely resilient, scalable, and adaptive security solution for modern smart home systems.

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.

Nektarios Deligiannakis, Vassilis Papataxiarhis, Michalis Loukeris, Stathes Hadjiefthymiades · 18 authors

Recently, the need for unified orchestration frameworks that can manage extremely heterogeneous, distributed, and resource-constrained environments has emerged due to the rapid development of cloud, edge, and IoT computing. Kubernetes and other traditional cloud-native orchestration systems are not built to facilitate autonomous, decentralized decision-making across the computing continuum or to seamlessly integrate non-container-native devices. This paper presents the Distributed Adaptive Cloud Continuum Architecture (DACCA), a Kubernetes-native architecture that extends orchestration beyond the data center to encompass edge and Internet of Things infrastructures. Decentralized self-awareness and swarm formation are supported for adaptive and resilient operation, a resource and application abstraction layer is established for uniform resource representation, and a Distributed and Adaptive Resource Optimization (DARO) framework based on multi-agent reinforcement learning is integrated for intelligent scheduling in the proposed architecture. Verifiable identity, access control, and tamper-proof data exchange across heterogeneous domains are further ensured by a zero-trust security framework based on distributed ledger technology. When combined, these elements enable increasingly autonomous workload orchestration, trading centralized control for adaptive, decentralized operation with enhanced interoperability, scalability, and trust. Thus, the proposed architecture enables self-managing and context-aware orchestration systems that support next-generation AI-driven distributed applications across the entire computing continuum.

Biru Rajak, Malik Bader Alazzam, B Karthikeyan, P N V Syamala Rao M · 6 authors

The scale of IoT and IIoT systems developing is growing rapidly since they deploy in critical infrastructure which also created major security issues such as data breaches, unauthorized access, and centralized model lack of trust issues. It is search of this study to formulate a block-chain-based IoT network that provides secure, trustful and corrupted-proof transmission of data. What is new in the approach is the combination of the use of machine learning-based real-time anomaly detection and the Ethereum-based smart contracts in the creation of a decentralized and intelligent security layer. In the offered framework, models XGBoost are trained using the Edge-IIoTset dataset with maximum accuracy of detection of 98%. Compared to traditional centralized and standalone ML-based solutions, the hybrid system is found to be much more efficient in both initial detection (precision), trust enforcement, and resilience. The findings ratify that the framework can be deployed in sensitive IoT/IIoT networks based not only on its ability to identify the source of cyber threats and curb them in real-time without necessitating any update, but also on its potential to increase the transparency and traceability of the network.

Zia Ullah, Zia Ullah, Sanam Shahla Rizvi, Ibrar Ali Shah · 5 authors

Vehicular Ad Hoc Networks (VANETs) are essential for the success of Intelligent Transportation Systems (ITS), providing real-time communication between vehicles and infrastructure. However, the highly dynamic and decentralized nature of VANETs introduces significant challenges in ensuring trust and security across the network, including security threats, communication overhead, and energy inefficiencies. This paper presents a novel blockchain-based trust management framework that addresses these issues by incorporating lightweight consensus mechanisms, optimized data propagation strategies, and energy-aware protocols. Our approach reduces communication overhead by selectively propagating trust updates, leading to a 35% decrease in overall network traffic compared to traditional broadcast-based systems. In terms of trust accuracy, our model achieves over 95% accuracy in detecting malicious nodes, significantly outperforming existing solutions. The proposed system demonstrates the identification and penalization of malicious behaviors such as Sybil attacks and false reporting with a 25% improvement in detection rate, while maintaining low latency (an average reduction of 30% compared to PoW-based systems) and efficient energy consumption, reducing energy use by up to 40%. The proposed model also incorporates a hybrid Proof of Stake (PoS) and Practical Byzantine Fault Tolerance (PBFT) consensus mechanism, which further enhances its scalability and fault tolerance. Simulation results show that our framework converges to accurate trust values faster than traditional methods, ensuring that reliable trust evaluations are made in real-time, even under high mobility conditions. The combination of these optimizations ensures that our framework is not only secure but also highly efficient, capable of supporting scalable and resilient VANET deployments. Furthermore, our decentralized approach ensures that trust decisions are made in real-time without the need for a centralized authority, making the system more adaptable to the high-mobility conditions of VANETs. This research offers a comprehensive solution for VANETs trust management, significantly improving communication efficiency, trust accuracy, and energy consumption while maintaining robust security and scalability. Our proposed blockchain-based trust management system provides a secure, energy-efficient, and scalable solution for VANETs, setting the stage for future developments in secure vehicular communication networks.

Hussein Othman, Fatima Abdallah, Mubarak Mohammad

In recent years, the adoption of the Internet of Things (IoT) has spread rapidly in various fields, enhancing technology and facilitating human life. To improve operational efficiency, user experience, and predictive maintenance of IoT applications, dynamic device recruitment and service provisioning are adopted instead of manual and fixed architectures. This raises challenges in adaptability, trust, and security, especially in heterogeneous environments such as smart cities. This paper utilizes blockchain and smart contracts to automate the process of IoT device recruitment and service provisioning. It proposes a decentralized architecture including a trust authority component for authentication, a smart contract generation component, and a negotiation component for dynamic contract refinement. This ensures a seamless and secure communication between the service provider and requester without reliance on third-party and manual intervention. The architecture components are presented in detail, and the full process from registration and authorization to dynamic contract generation and negotiation is then explained. It shows how manual intervention is reduced while ensuring trust and adaptability. Future work includes model formalization, prototype implementation, and performance evaluation.

Dinesh Kumar Arivalagan, Sathiyandrakumar Srinivasan

This interdependent network of vehicles has been made possible by the widespread adoption of self-driving cars operating as interconnected swarm networks based on continuous data exchange. Leading a Data-Driven Paradigm Shift However, these networks are not without their challenges, as they are prone to security threats, data privacy vulnerabilities, and inefficient consensus mechanisms to facilitate decentralized decision-making. This study proposes a novel blockchain architecture using AI that could offer enhanced security by utilizing a hybridized consensus protocol for autonomous vehicles. Accordingly, machine learning algorithm-based optimizations in blockchain consensus algorithms, such as PoW, PoS, and DPoS consensus methods, facilitate real-time adaptive adjustments, lower mining costs, and accelerated transaction validation, all within the framework of decentralized trustworthiness. In self-driving car ecosystems, AI-augmented security processes like anomaly detection, deep learning-based intrusion prevention, and federated learning, enhance threat detection while lowering the cybersecurity risks. Moreover, privacy-enhancing cryptographic methods, such as homomorphic encryption, zero-knowledge proofs (ZKPs), and differential privacy, are incorporated to safeguard sensitive vehicle information against unauthorized access while allowing compliance with data privacy laws. Experimental evaluations confirm that the proposed AI-empowered frameworks lead to improved system resilience, optimized resource allocation and improved transaction throughput and latency in contrast to traditional blockchain implementations. Overall, this study demonstrates that using AI-enabled blockchain models can provide a fundamental method for protecting and improving autonomous vehicle networks.