# Security Threats in Intelligent Transportation Systems and Their Risk Levels
## 5 Countermeasures
This model constructed the virus propagation process in the upper layer using Susceptible-Infectious-Recovered (SIR) model KERMACK199133. Several results were obtained: (i) Communication range and travel distance of infected vehicles are proportional to the probability of virus infection. In contrast, increasing traffic density decreases the probability of virus infection. This result somewhat contrasts theories of disease-spreading. (ii) The higher the probability of virus infection, the shorter the time required for the virus to spread to the epidemic stage. This makes perfect sense in terms of epidemic models. (iii) There are certain minimum proliferation thresholds for viruses. (iv) Reducing the probability of virus infection is essential for virus management under various constraints of communication range and traffic levels. In [PERSON] et al. (2021), the authors propose a mathematical model called SEIR-S (Susceptible, Exposed, Infectious, Recovered-Susceptible) based on VANET characteristics and the SIR disease propagation model. This model takes into account the possible behaviors of malware and provides the corresponding states of the vehicles: Susceptible (S), Exposed (E), Infectious (I) or Recovered (R). Some studies focus on the impact of worm propagation and factors affecting malware propagation on V2X communications and propose similar worm models ([PERSON] and [PERSON] (2019); [PERSON] et al. (2018)). In a blackhole attack, instead of relaying network traffic to destinations, the malicious node drops the packets and prevents traffic from flowing. Therefore, the goal of a blackhole attack (also referred to as a packet-drop attack) is to persuade as many nodes as possible to send their traffic through the malicious node. As a result, the communication between the source and the destination is blocked ([PERSON] et al., 2017; [PERSON] et al., 2019). To overcome this issue, a secure AODV routing protocol was developed for detection of blackhole attacks by [PERSON] et al. (2021). The proposed method is a modified version of the original AODV routing protocol with improvements in the RREQ packet and RREP packet protocols. For added security, cryptographic function-based encryption and decryption is included to verify the source and destination nodes. As this type of attack is classified as critical risk, the risk must be treated as urgent and appropriate countermeasures must be developed. After performing the ITS risk assessment using TVRA and determining the risk level of each threat, we chose the proposal in [PERSON] et al. (2021) as a trusted and secured extension of OLSR protocol to mitigate the risk of blackhole attacks in VANET. The system proposed in [PERSON] et al. (2021) provides all vehicles in the network with a commonly distributed, highly secure, tamper-proof framework for routing in VANETs using blockchain. We use Optimized Link State Routing (OLSR) as a characteristic routing protocol to integrate blockchain into VANETs. OLSR has various security issues because its routing mechanism is based on the availability of a small group of nodes called multi-point relays (MPRs), and the security mechanisms are executed at each node individually with repetitive processes. In our proposed contribution, we use blockchain, as a reliable and highly secure technology to solve the security problems of OLSR by motivating (rewarding) the vehicles to collaborate and avoiding repetitive detection processes.