# Distributed Reputation for Accurate Vehicle Misbehavior Reporting (DRAMBR)
## 3 Related Work  
This section analyzes the use of reputation systems in misbehavior reports and feedback mechanisms conducted in recent studies to maintain network trustworthiness and security in both connected and disconnected areas. In recent years, there has been significant research interest in using reputation systems to minimize malicious behaviors for trustworthy V2V communications. To illustrate, reputation-based malicious vehicle detection systems have been devised and are gaining popularity to effectively deal with the threat of malicious vehicles in vehicular networks. The source vehicle determines whether a vehicle is dangerous based on its reputation score and then finds a trusted communication path. A key point to remember is that V2V reputation research is categorized into centralized and decentralized models. The centralized approach, pioneered by [18], revolves around a scheme that centrally distributes, updates, and stores vehicles' reputation scores. That study introduces a reputation announcement scheme for VANETs using Time Threshold to assess message reliability. The researchers in [19] recently proposed a centralized system for highways and urban roads, relying on a central Trusted Authority to calculate feedback scores from various vehicles and update the target's reputation. Moreover, Ref. [20] proposed an incentive provision method in which the RSU updates the sender's reputation score based on observed actions validated by vehicles. In contrast, distributed reputation systems operate without dependence on infrastructure. In this model, vehicles autonomously collect, maintain, and update reputation scores in an ad hoc manner. The authors in [21] developed a node reputation system to evaluate the reliability of vehicles and their messages. They grouped vehicles with similar mobility patterns that are close to each other into platoons to minimize propagation overhead. In 2021, [PERSON] et al. [22] introduced a framework for self-organized vehicles that filters out malicious vehicles based on standard scores. In 2014, [PERSON] et al. presented a multihop version that utilized the carry-and-forward method [23]. The ideas aim to assess the message's reliability and the aggregation of reputation scores. In contrast, [PERSON] et al. proposed a single-hop version that employed a single-hop reputation announcement [24]. However, because messages and feedback are linked and not anonymous, these schemes do not provide enough privacy protection. As a result, an attacker can carry out a traceability attack and learn the path of a target vehicle. Taking into account the vehicle's reporting history, these reputation systems improve the accuracy of accident detection. The work by [PERSON] introduced a dynamic reputation scheme based on events that assigns reputation value according to the vehicle's behavior [25]. Reputation values are awarded to each vehicle that sends messages that corroborate with other vehicles, which increases the vehicle's trust degree with each verified message. However, this scheme is insufficient in mitigating the threat posed by Sybil attacks, where a malicious vehicle might have multiple fake identities to send false messages. Two-pass validation and a two-phase transaction were included in the blockchain-based traffic event validation that the authors of [26] suggested. They employed a consensus mechanism referred to as a Proof of Event, which employs two criteria. Vehicles send alerts to the RSU, which only takes them for a set amount of time. The RSU enters the notification phase once the number of alerts exceeds the first threshold. With the assistance of approaching vehicles, it can validate the alert, add it to the local blockchain, and use multi-hop transmissions to notify neighboring vehicles about the incident. Once all RSUs have agreed that the incident is correct and have reviewed the supporting evidence and reports, the RSU notifies the other RSUs in the same zone. The occasion will be appended to the worldwide blockchain, including all local happenings.