TL;DR
This paper proposes a secure and collaborative computation offloading framework with dynamic service caching in blockchain-empowered UAV-assisted vehicular networks, which consists of offloading decision making, dynamic service caching and caching updating decisions, computation resource allocation, and blockchain consensus mechanism.
The Internet of Vehicles (IoV) enhances road safety and supports autonomous driving through real-time communication, but current methods face key challenges: rigid resource allocation due to static architectures, communication failures in low-signal areas from infrastructure reliance, and passive defense mechanisms struggle to counter coordinated attacks, while high-latency encryption algorithms further compromise framework real-time performance. To address this, we propose a blockchain-based dynamically adaptive restructuring framework. It enables real-time IoV cluster restructuring by splitting overloaded IoVs to reduce communication overhead, or merging nearby IoVs to optimize resource utilization. In infrastructure-sparse zones, vehicles establish temporary multi-hop communication links based on relative mobility to ensure continuous connectivity. A multi-layered security mechanism integrates physical validation, event verification, and majority voting, achieving over 95% resistance to data tampering. Compared to Raft, PoS, and PBFT, our framework improves consensus speed by 27.06%–38.56%, and reduces transaction latency by 7%–35%, 15%–54%, and 27%–66%, respectively. It also maintains high robustness under dense traffic, high mobility, and weak signals, offering a proactive, adaptive security paradigm for intelligent transportation frameworks.
The rapid growth of Internet of Things (IoT) systems has introduced significant challenges related to privacy, trust, scalability, and attack resilience, particularly in resource-constrained and location-sensitive environments. Existing blockchain consensus mechanisms provide decentralised trust, but they often suffer from high communication overhead, weak physical-context awareness, and limited privacy protection when deployed in large-scale IoT networks. This paper proposes Elastic Proof-of-Location Byzantine Fault Tolerance (EPoLBFT), a privacy-preserving and location-aware blockchain consensus framework for IoT systems. The proposed design enables IoT nodes to prove regional eligibility without revealing exact coordinates while restricting consensus participation to trusted and geographically verified validators. EPoLBFT is evaluated using the Blockchain IoT Consensus Algorithm (BICA) simulator under normal, high-load, Byzantine, Sybil, location-spoofing, and denial-of-service scenarios. The evaluation considers latency, throughput, communication overhead, energy consumption, and attack resilience. The results show that EPoLBFT reduces communication overhead and improves consensus efficiency compared with conventional PBFT-based approaches while strengthening resilience against location-based and identity-based attacks. The study also discusses the privacy–latency trade-off introduced by zk-PoL, the assumptions related to trusted location anchors, and the limitations of simulation-based evaluation.
The rapid development of the Internet of Things (IoT) has placed considerable pressure on both security and stability in heterogeneous, resource-constrained networks. In such dynamic environments, trust management is a central issue to determine which service providers can be trusted and to combat malicious activity. Although blockchain-based solutions have offered a means for decentralized, tamper-resistant trust management, most rely on classical cryptographic primitives, which are vulnerable to future quantum computing attacks. This study proposes a Quantum-Resistant Blockchain-Based Trust Management (QR-BCTM) framework in which Post-Quantum Cryptographic mechanisms, Permissioned Blockchain Platform, and Fog-assisted Trust Management architecture are combined and utilized in IoT networks. The framework introduces a quantum-aware trust computation model that combines behavioral trust, indirect recommendations, and a cryptographic assurance score quantifying each participant’s compliance with security requirements. Trust evidence is compressed to reduce blockchain storage and communication overhead, while the hierarchical fog-blockchain architecture offloads computationally intensive operations from resource-constrained IoT devices. The performance of the framework has been simulated in the presence of an adversary, including bad-mouthing, ballot-stuffing, on-off behavior, and identity attacks using a Sybil-type mechanism. Trust accuracy, false trust acceptance, communication overhead, and computation cost were measured, and a sensitivity analysis on the trust-weight parameters was performed. The simulation results suggest that QR-BCTM can enhance the accuracy of trust evaluation, mitigate the impact of malicious nodes, and remain scalable and efficient despite the existing cryptographic overhead. Post-quantum digital signatures and formal security analysis provide protection against quantum-era threats and attacks, while classical threats are mitigated through behavioral trust aggregation and recommendation filtering. In summary, QR-BCTM provides a scalable, simulation-validated and quantum-aware framework for trustworthy IoT network operation, offering practical guidelines for future deployment and prototyping.
Internet of Vehicle (IoV) uses heterogeneous access technologies to link automobiles and their surroundings. Effective methods are essential for safeguarding data confidentiality and privacy during communication among the roadside unit (RSU), the control room, and vehicles. Many vehicle-to-infrastructure authentication-based approaches have been developed to secure the IoV environment. However, efficiency and security are challenged by instability, decentralization, and transaction-tracking features. To resolve this, a secure, lightweight, and scalable communication protocol was developed for a 5G-enabled SDN-IoV environment. Efficient block verification is achieved through the Joint-Graph Delegated Practical Byzantine Fault Tolerance (JtGr-DPBFT) mechanism, in which validators create subgraphs to reduce communication overhead. JtGr-DPBFT is combined with an Improved Gossip Algorithm (IGA) to minimize message redundancy and optimize bandwidth utilization. Moreover, a lightweight hierarchical authentication mechanism, assisted by a Merkle Tree with Boneh-Lynn-Shacham (HAMT-BLS) signatures, enables compact block verification and minimizes computational and communication costs. The proposed model achieves tamper-proof, efficient, and scalable block verification by incorporating hierarchical authentication with consensus optimization. This approach is simulated in the NS3 tool, and performance is evaluated in terms of propagation delay, transaction confirmation latency, throughput, communication cost, and network delay. Thus, secure and tamper-proof communication is developed to ensure integrity, trust, and dependability in the SDN-enabled IoV environment.
The vehicular ad-hoc network (VANET) provides a way for drivers or vehicles to communicate with each other in a more effective manner, however, there are still many issues with respect to different aspects of security, trust management, and delivering information reliably between two nodes. This study presents a way to facilitate Security in a VANET through a Trust-Aware, Block chain-Supported Information-Centric Networking (ICN) Framework. This Framework allows for more efficient dissemination of secure information in VANETs, making use of the requested/forwarding of Content In-Networks by Caching, which ideally would provide fast access to content and maintain availability and reduced latency for users within the network. A Trust Evaluation Module is employed to determine Node Behavior via the Packet-Forwarding Ratio of Nodes as well as the Validity of Packet-Content being forwarded. Blockchain Technology is used to hold Trust Records using PBFT Consensus, where records of malicious nodes identified. Lastly, Adaptive Trust Thresholds, Probabilistic Caching, and Malicious Content Filtering are utilized for Trust-Aware Forwarding and Caching mechanisms based upon calculated Trust Values with the intent to ensure the delivery of verified Data and to improve Network Performance. Simulation results show that the proposed method achieves a PDR of 98%, higher throughput, reduced delay, and lower packet loss compared to existing approaches, confirming its effectiveness in providing secure and reliable VANET communication under attack conditions.