Enhancing Intelligent Transport Systems Through Decentralized Security Frameworks in Vehicle-to-Everything Networks

World Electric Vehicle Journal, Год журнала: 2025, Номер 16(1), С. 24 - 24

Опубликована: Янв. 3, 2025

Vehicle Ad hoc Networks (VANETs) play an essential role in intelligent transportation systems (ITSs) by improving road safety and traffic management through robust decentralized communication between vehicles infrastructure. Yet, decentralization introduces security vulnerabilities, including spoofing, tampering, denial-of-service attacks, which can compromise the reliability of vehicular communications. Traditional centralized mechanisms are often inadequate providing real-time response scalability required such dispersed networks. This research promotes a shift toward distributed technologies, blockchain secure multi-party computation, to enhance integrity privacy, ultimately strengthening system resilience eliminating single points failure. A core aspect this study is novel D-CASBR framework, integrates three components. First, it employs hybrid machine learning methods, as ElasticNet Gradient Boosting, facilitate anomaly detection, identifying unusual activities they occur. Second, utilizes consortium provide transparent information exchange among authorized participants. Third, implements fog-enabled reputation that uses fog computing effectively manage trust within network. comprehensive approach addresses latency issues found conventional while significantly efficacy threat achieving 95 percent detection accuracy with minimal false positives. The result substantial advancement securing

Язык: Английский

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Federated Learning-Based Predictive Traffic Management Using a Contained Privacy-Preserving Scheme for Autonomous Vehicles

Sensors, Год журнала: 2025, Номер 25(4), С. 1116 - 1116

Опубликована: Фев. 12, 2025

Intelligent Transport Systems (ITSs) are essential for secure and privacy-preserving communications in Autonomous Vehicles (AVs) enhance facilities like connectivity roadside assistance. Earlier research models used traffic management compromised user privacy exposed sensitive data to potential adversaries while handling real-time from numerous vehicles. This introduces a Federated Learning-based Predictive Traffic Management (FLPTM) system designed optimize service access within an ITS. Moreover, CPPS will provide strong security mitigate adversarial threats through state modelling authenticated permissions the integrity of vehicle communication networks man-in-the-middle attacks. The suggested FLPTM utilizes Contained Privacy-Preserving Scheme (CPPS) that decentralizes processing allows vehicles train local without sharing raw data. framework combines classifier-based learning technique with protect against invasions proposed model leverages Learning (FL) collaborative machine processes by allowing updates preserve privacy, enabling joint exposing It addresses key challenges such as high costs, impact attacks, time inefficiencies. Using FL, reduces costs 23.29%, mitigates effects 16.1%, improves 18.95%, achieving significant cost savings maintaining throughout process.

Язык: Английский

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Dual-Policy Attribute-Based Searchable Encryption with Secure Keyword Update for Vehicular Social Networks

Electronics, Год журнала: 2025, Номер 14(2), С. 266 - 266

Опубликована: Янв. 10, 2025

Cloud-to-Vehicle (C2V) integration serves as a fundamental infrastructure to provide robust computing and storage support for Vehicular Social Networks (VSNs). However, the proliferation of sensitive personal data within VSNs poses significant challenges in achieving secure efficient sharing while maintaining usability precise retrieval capabilities. Although existing searchable attribute-based encryption schemes offer encrypted fine-grained access control mechanisms, these still exhibit limitations terms bilateral control, dynamic index updates, search result verification. This study presents Dual-Policy Attribute-based Searchable Encryption (DP-ABSE) scheme with keyword update functionality VSNs. The implements decoupling mechanism that decomposes attributes into two distinct components: immutable attribute names mutable values. decomposition transfers verification process from owners files themselves, enabling attribute-level granularity control. Through an identity-based authentication derived owner’s unique identifier bilinear pairing verification, it achieves updates specified keywords preserving both anonymity non-updated confidentiality message content. employs offline/online two-phase design, allowing pre-compute ciphertext pools real-time encryption. Subsequently, decryption introduces outsourcing local-phase mechanism, leveraging key encapsulation technology computation outsourcing, thereby reducing terminal computational load. To enhance security at stage, incorporates module based on correlation validation, preventing replacement attacks ensuring integrity. Security analysis under standard assumptions confirms theoretical soundness proposed solution, extensive performance evaluations showcase its effectiveness.

Язык: Английский

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<i>k</i>-anonymity in Resource Allocation for Vehicle-to-Everything (V2X) Systems

Journal of Telecommunications and Information Technology, Год журнала: 2025, Номер unknown, С. 1 - 4

Опубликована: Фев. 10, 2025

Sixth generation (6G) vehicle-to-everything (V2X) systems face numerous security threats, including Sybil and denial-of-service (DoS) cyber-attacks. To provide a secure exchange of data protect users' identities in 6G V2X communication systems, anonymization techniques - such as k-anonymity can be used. In this work, we study centralized vs. based resource allocation methods vehicular edge computing (VEC) network. Allocation decisions for networks are classically posed optimization task. Therefore, an information flow is transmitted from the vehicles to premises. addition decision, vehicle not required. We analyze versus k-anonymous models. show potential deterioration introduced by anonymity, quantify gap optimal goal two cases: on with aim at energy reduction. Our numerical results indicate that consumption rises 1% smaller scenarios 23% medium scenarios, whereas it decreases 14% larger scenarios.

Язык: Английский

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A Survey on Distributed Approaches for Security Enhancement in Vehicular Ad-hoc Networks

Computer Networks, Год журнала: 2025, Номер unknown, С. 111140 - 111140

Опубликована: Фев. 1, 2025

Язык: Английский

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Multi-Agent Reinforcement Learning for task allocation in the Internet of Vehicles: Exploring benefits and paving the future

Swarm and Evolutionary Computation, Год журнала: 2025, Номер 94, С. 101878 - 101878

Опубликована: Фев. 20, 2025

Язык: Английский

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A multi-objective approach for secure cluster based routing & attack classification in VANETs

Peer-to-Peer Networking and Applications, Год журнала: 2025, Номер 18(3)

Опубликована: Март 11, 2025

Язык: Английский

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Ensuring Trustworthy and Secure IoT: Fundamentals, Threats, Solutions, and Future Hotspots

Computer Networks, Год журнала: 2025, Номер unknown, С. 111218 - 111218

Опубликована: Март 1, 2025

Язык: Английский

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False Information Mitigation Using Pattern-Based Anomaly Detection for Secure Vehicular Networks

Electronics, Год журнала: 2025, Номер 14(9), С. 1848 - 1848

Опубликована: Май 1, 2025

Vehicular networks utilize wireless communication among vehicles and between infrastructures. While vehicular offer a wide range of benefits, the security these is critical for ensuring public safety. The transmission false information by malicious nodes (vehicles) selfish gain issue in networks. Mitigating essential to reduce potential risks posed Existing methods detection various approaches, including machine learning, blockchain, trust scores, statistical techniques. These often rely on past about vehicles, historical data training learning models, or coordination without considering trustworthiness vehicles. To address limitations, we propose technique False Information Mitigation using Pattern-based Anomaly Detection (FIM-PAD). novelty FIM-PAD lies an unsupervised approach learn usual patterns direction travel speed variations vehicles’ speeds different directions. uses only real-time network characteristics detect that do not conform identified patterns. objective accurately with minimal processing delays. Our performance evaluations high proportions confirm average offers 38% lower delay at least 19% positive rate compared three other existing

Язык: Английский

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Third layer blockchains are being rapidly developed: Addressing state-of-the-art paradigms and future horizons

Journal of Network and Computer Applications, Год журнала: 2024, Номер unknown, С. 104044 - 104044

Опубликована: Окт. 1, 2024

Язык: Английский

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