# Distributed Reputation for Accurate Vehicle Misbehavior Reporting (DRAMBR)
## 4 System Model
### Workflow and DRAMBR Phases
#### 4.4.1 Process 1: Offline Evaluation (OE)
In this stage, preliminary misbehavior reports are generated based on immediate surroundings (direct observation) or V2V communications(Indirect observation). The LMDM \begin{table}
\begin{tabular}{c l} \hline \hline
**Notations** & \(Rep_{\textbf{veh}}\)**Action** \\ \hline O(R) & Observing misbehavior and generating \(MR\). \\ \hline O(NR) & Observing misbehavior but not generating a \(MR\). \\ \hline O(NMR) & Not observing misbehavior but generating a \(MR_{f}\). \\ \hline O(NNMR) & Neither observing nor generating. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: \(Rep_{\textbf{veh}}\) Observing Misbehavior Action. Figure 9: Local Misbehavior Detection Mechanism (LMDM). outputs serve as inputs to the DRAMBR OR process. LMDM includes five main steps, as explained below:  
1. Detection: The OBUs of the evaluator (\(V_{i}\)) actively detect and identify irregularities and potential misbehavior within the network. 2. Evaluation: \(V_{i}\) evaluates the misbehavior to decide whether or not to generate an MR for the observed misbehavior event. To confirm the misbehavior through collective evaluation, \(V_{i}\) communicates with nearby vehicles if any are present. If no other vehicles are available in the area for verification, \(V_{i}\) proceeds to make an independent decision based on the available evidence. This approach has been discussed in [44], where vehicles collaborate to validate suspicious activities. 3. Decision: In this phase, \(V_{i}\) creates the MR based on the gathered information provided by the local misbehavior detection service and optionally of other evidence obtained from other vehicles. 4. Storage: \(V_{i}\) stores MR to either share it with other nearby vehicles or to submit it later to the RS upon connectivity. 5. Transmission: After MR creation, \(V_{i}\) decides whether to share the MR with other nearby vehicles or to store it. If multiple MRs are available to send, \(V_{i}\) has to decide which ones to send and in which order. It is worth noting that during the LMDM process, we add the key functional component State. As outlined in the ITS standards [17], this is responsible for storing and managing information used by other parts of the system. It manages three key factors:  
* MR Creation: Allocates processor time and signing resources amid competing demands. * Storage: Ensures MRs fit within available storage, prioritizing critical ones. * Transmission: Manages limited connectivity, prioritizing essential MRs for timely transmission. In the current state of the ITS standards [17], every false message \(M_{sg}\) flagged as misbehaving is reported. However, not every \(M_{sg}\) should be separately reported as this would cause a significant network overhead, particularly when the misbehavior is a result of a faulty component in its system. Consequently, the MR format allows for omitted MRs, which means that the \(Rep_{\text{Veh}}\) temporarily stops generating repeated MR for the exact \(Tar_{\text{Veh}}\) about the same misbehavior after detecting it. Instead, it continues collecting relevant evidence over time. Once enough proof is gathered, the \(Rep_{\text{Veh}}\) generates a single, detailed MR to the RS. The protocol assumes that the RS is capable of prioritizing the quality and significance of the MR's content, rather than just counting how many MRs it receives. This method increases reporting efficiency and decreases redundant communications.