## 3 Related Work  
The intersection of blockchain technology, artificial intelligence, and autonomous vehicle (AV) security has attracted considerable attention in recent years, particularly in securing vehicle communications and mitigating cyber threats. Vehicular ad hoc networks (VANETs) and vehicle-to-everything (V2X) communications provide the basis for real-time  
Figure 3: Illustration of a Sybil attack in a vehicular network. A malicious vehicle (red car) creates multiple fake identities to inject false information into the network, misleading nearby vehicles and disrupting communication. Examples include spoofed hazard warnings, false location data, and network congestion, which compromise the safety and trustworthiness of vehicle-to-vehicle (V2V) communication. Figure 2: Types of denial-of-service (DoS) attacks in vehicular communication systems: (a) packet flooding, (b) V2V radio jamming, and (c) V2I radio jamming. peer-to-peer interaction between AVs, but they also expose these networks to vulnerabilities such as Sybil attacks and denial-of-service (DoS) attacks. Traditional centralized security methods have proven inadequate for the size and complexity of AV networks. Therefore, researchers have explored the decentralized ledger of the blockchain as a solution for securing data integrity and vehicle authentication [2; 5]. The integration of the blockchain with AI has shown promise in strengthening the resilience of vehicle networks. Studies suggest that the consensus mechanisms Byzantine Fault Tolerance (BFT) and Practical Byzantine Fault Tolerance (PBFT) [12] increase security against identity spoofing attacks, a common problem in V2X networks [13]. In a recent study [14] applied these protocols in blockchain architectures and demonstrated their effectiveness in maintaining network reliability, even in scenarios with malicious nodes. To mitigate latency issues, fog and edge computing models are often used alongside the blockchain. These approaches help reduce the computational load by distributing tasks to roadside units (RSUs) close to data sources, thus meeting the real-time processing requirements for AVs [15]. In one case, [PERSON] et al. (2023) integrated [8] RSUs with lightweight blockchain clients to enable localized data validation and ensure faster decision making in dynamic environments such as V2I communication. In addition, smart contracts play a crucial role in automating secure transactions in these networks, where they help maintain transparency in data sharing and manage privacy controls that are essential for regulatory compliance in vehicular communication systems [16]. Recent work by [PERSON] and [PERSON] (2024) [17] has shown that smart contracts can effectively regulate the interaction of AV data by providing decentralized access only to authorized entities. The privacy mechanisms in these contracts, which are often reinforced by cryptographic algorithms such as Elliptic Curve Cryptography (ECC) [18], further protect user data. As blockchain and AI technologies mature, studies are increasingly focusing on optimizing these systems for large-scale use, especially in the context of smart cities. Challenges such as scalability and energy efficiency [19] remain at the forefront, with researchers proposing adaptive strategies such as sharding and lightweight consensus models to efficiently process large amounts of data [20; 21]. These advances not only contribute to scalability but also improve fault tolerance in AV networks, where maintaining low latency is critical to vehicle responsiveness and user safety. While previous research has made significant strides in integrating blockchain and artificial intelligence (AI) to enhance vehicular network security, several critical challenges remain. Many studies focus on specific security threats, such as Sybil attacks or denial of service (DoS) attacks, without addressing the scalability and real-time processing requirements essential for practical deployment in dynamic vehicular environments.