## 2 Related Works  
However, although IoV networks are becoming an important component of traffic safety in smart cities, the problem of cybersecurity is far from being solved. This is due to the fact that VANET uses an open broadband radio channel for data exchange. This contributes to the presence of a large number of cyberattacks, which can be categorized into several groups. The first group includes attacks on availability. The description of Denial-of-Service (DOS) attacks as well as methods for counteracting them are presented in [18]. One of the effective ways to disrupt data exchange between OBUs and RSUs is jamming. The paper [19] provides descriptions of jammers and also presents methods for counteracting them. To effectively utilize IoV technologies, the problem of privacy breaches must also be addressed. In [20], a rather detailed analysis of the main attacks on vehicle privacy as well as solutions to this problem is presented. Thus, both cryptographic methods [21] and noise techniques [22] are used against eavesdropping and traffic analysis. Nowadays, there has been an increase in the number of privacy attacks related to revealing the current location of a vehicle or tracking its trajectory. The main approach to ensuring the privacy of vehicle owners when using local-based services (LBSs) is based on the concept of k-anonymity. In order to implement k-anonymity, ref. [23] proposes creating groups in which all users have similar profile attributes. The use of clustering techniques can also improve the resilience to privacy attacks. In this case, vehicles are grouped into clusters according to some set of rules. In each cluster, a clusterhead (CH) is selected to communicate between clusters. In [2], in order to provide stable confidential communication with clusters, the locations of the CH must be precisely determined. To solve this problem effectively, the authors propose using a Back Propagation Neural Net work (BPNN) combined with the distributed gradient incidence method. Also, to ensure privacy, pseudonyms are proposed in [24]. In order to ensure privacy in vehicle-to-vehicle communication in VANET, a number of works propose the use of reputation management schemes. Reputation schemes allow the information source to provide more efficient confidential data transmission. In [25], the application of a reputation management scheme in cloud-based vehicular networks is discussed. Currently, reputation updates are performed by a trusted authority (TA) after collecting, transcribing and verifying a large number of reputation feedbacks, which results in high computational and communication overhead on the part of the TA. To reduce the computational complexity, the authors propose pre-processing the data by a cloud service provider (CSP). Elliptic curves and a homomorphic Paye encryption algorithm are proposed to increase the privacy level. The developed privacy-preserving reputation updating scheme provides the secure privacy preservation of a unique identifier, reputation and vehicle feedback score using cryptographic techniques only. The problem of privacy assurance in the transmission of emergency messages in VANET through the use of a trust management scheme is considered in [26]. In this paper, a novel cascaded trust cascading-based emergency message dissemination (TCEMD) model is proposed, which effectively combines object-oriented trust values with data-oriented trust evaluation (annotation). According to the TCEMD model, emergency messages are propagated through vehicles that need to trust each other. To fulfill this condition, trust certificates are currently applied, which are issued to each vehicle by a centralized authority (CA). A PKI scheme is used to obtain the certificate of trust, and each emergency message is signed with the electronic digital signature of the legal vehicle. The Space-Air-Ground Integrated Network (SAGIN) allows for extending the application of IoV and improving the performance of transportation networks. Several trust management schemes have been developed for SAGIN [27; 28].