# An Efficient Trust-Based Scheme for Secure and Quality of Service Routing in MANETs
## 2 Related Work  
[PERSON] et al. proposed a new routing protocol by extending the conventional Ad Hoc On-Demand Distance Vector (AODV)called (TRUST_AODV) [7], incorporating a trust algorithm that detects misbehaving nodes within. An objective trust management framework is used in this approach for solving problems such as handling high node mobility, energy drain, and limited processing capabilities of network devices by establishing a network of nodes with an acceptable level of trust relationships among themselves. The weighted trust is computed for each node, by the proposed algorithm considering the packet delivery ratio, energy consumption rate and buffer length into account. The Overall performance of TRUST_AODV routing protocol indicates that it secures the MANET against potential packet drop attacks and denial-of-service (DoS) attacks. [PERSON] et al. proposed an opinion based trust model which works on the basis of network properties [3]. In this solution, intermediate nodes' opinion trust is computed and based on suchan opinion trust value, the decision can be made regarding the use of a particular route for communication. Communication in MANETs has to be carried out through using intermediate nodes due to limited radio range. As a result, malicious nodes can join the network and harm the routing process. Thus, trust evaluation can yield two values at the minimum: negative and positive, in the process of finding a trustworthy node. After deriving the trust values for all the nodes along a path, route discovery can be performed by taking the opinion of the neighboring nodes. [PERSON] et al. proposed a model that deploys security in MANETs while taking into consideration of QoS issues to some extent [8]. The proposed model is multilayered and composed of a set of modules, i.e., packet receiver, packet forwarder, QoS routing module (RM), system security module (SSM) and data security module (DSM). All the modules are needed in order to identify QoS parameters and to detect selfish and malicious nodes. Efficient and reliable communication is ensured by selecting an appropriate router between a source and a destination through trusted nodes in the place of eliminated nodes. Performance evaluation was done in an established secure environment to show the improvement over AODV for different QoS parameters for both single and multi-path environments. [PERSON] et al. proposed a composite trust model which utilized both social and QoS trust components [11] to estimate the trust degree of nodes in which the ditch ratio was used as a social trust component. This ditch ratio parameter is valuable for knowing the behavior of nodes and to identify malicious nodes. In the paper, energy consumption was defined as an aspect of QoS by considering the ratio of packet drop of a specific node. Nodes with the lowest level of energy are considered as un-trusted nodes. The proposed scheme showed some enhancement in packet delivery ratio when compared to some other methods. [PERSON] et al. proposed a method to evaluate the trust value of a node based on its quality of service (QoS) parameters [15] where fuzzy rules were inferred based on network conditions. The proposed method used an algorithm based on Dynamic Adaptive Fuzzy Petri Net (DAFPN) with concurrent reasoning. DAFPN is an expert system to represent, capture and store fuzzy knowledge with the help of parameters such as threshold value, certainty factor and weight. The concurrent reasoning algorithm (CRA) is a matrix operation based algorithm, which can automate the procedure of DAFPN in which a MANET topology was modeled as a DAFPN to which FPN rules were applied. Route identification and recovery mechanisms with CRA used unicast and multicast methods and the proposed method included all the trustable intermediate nodes for routing. [PERSON] et al. proposed an algorithm that used a management strategy for trust in a way in which packets can be sent securely through the network with a lower level of energy consumption [17].