## 9 Related Work
### Trust Establishment and Management in Ad Hoc Networks  
Trust management can help in building cooperation with unknown nodes to access the various observations and based on this make a reputation system to rank a good and badly behaved vehicle. The reputation system can be categorized to make sure credibility on which vehicle to cooperate with, and even to punish the untrusted vehicle. In our 3 VSR, we have used two kind of sensing between neighbor vehicles, one is direct sensing that is comes from self experience with neighbor vehicle or through passive collection of some evidence by putting node into promiscuously mode or by packet acknowledgment in route discovery process. The second kind of sensing is indirect observation, it comes from one to many users as generally advise by fried or neighbor for a particular node. The indirect observation can be collected through surveys, monitoring past behaviors and recommendation of others. The main drawback of indirect observations are related to overhead, false report, trust distortion and collusion attacks [34].  
Meanwhile, previously proposed secure routing protocols like CONFIDANT in [35] (Cooperation Of Nodes, Fairness In Dynamic Ad-Hoc Networks), to encourage the node cooperation and punish malicious nodes. A possible drawback of CONFIDANT is that an attacker may intentionally spread false alerts to other nodes that a node is misbehaving while it is actually a well-behaved node. [PERSON] et al. [36] presented a solution called CORE to identify selfish nodes, and then compel them to cooperate in the following routing activities. Similar to CONFIDANT, CORE uses both a surveillance system and a reputation system to observe and evaluate node behaviors, but CORE only uses positive observation to be shared among nodes, this way, malicious nodes cannot spread fake charges to frame the well-behaved nodes. [PERSON] et al. [37] studied an approach in which the reputation of a node is determined by data validation. In this approach, a few nodes, which are named as Anchor nodes here, are assumed to be reliable, and thus the data they provide are regarded as trustworth. In addition, there have been some other research efforts that aim to enhance the security, trust and privacy in ad hoc networks [38; 39].  
In addition, most of the existing trust management methods for ad hoc networks focus on assessing the trustworthiness of mobile nodes by collecting multiple evidences and analyzing behavioral history of the nodes. However, little attention has been paid to evaluate the trustworthiness of the data shared among these nodes and uncertainty management. Further, the lower uncertain values leads to high confidence in data shared between these distributed vehicles. Starting fromprobabilistic subjective logic, which comes up as promising technique to manage uncertainty between distributed nodes [40; 41]. [PERSON] et al. in [42] used subjective logic as advantage for forward node selection using trusted routing, which reduces extra computation and routing overhead. Some researchers also make use of fuzzy theory as logical reasoning [43]. These works contribute a lot to solve the uncertainty problem, although uncertainty generated as result of trust propagation rarely counted. Comparing to subjective logic, sensing logic distinguishes certain evidences that are distorted and transferred into the neutral state, referred as posterior uncertainty. Sensing logic also considers trust as distortion if it comes from one to many users as recommendation and separate them as original and distorted opinion by using Lemma 1, that already discussed in Section 5. Therefore, we rely on this new sensing logic for accurate trust assessment in vehicular ad hoc networks.