Title | Algorithm | Concept | Issues |
---|---|---|---|
Security through collaboration and trust in MANETs [38] | Gossip-based outlier detection algorithm | • Outlier detection uses local view formation, local view exchange, local view update, and global view formation | Longer time to converge to a global view if more nodes in MANET |
Trust evaluation in wireless ad hoc networks using the fuzzy system [48] | Fuzzy trust algorithm | • Calculates the trust level of a route from source to destination | Suitable only for low mobile ad hoc networks |
Friend-based ad hoc routing using challenges to establish security in MANET system [37] | FACES algorithm | • Sends challenges and shares friend lists to provide a list of trusted nodes to the source node through which data transmission finally takes place | More control overhead due to challenge request and challenge reply |
Outlier detection using naïve Bayes in wireless ad hoc networks [49] | Naïve Bayes classifier | • Predicts the reliability of trust information provided by other adjacent nodes | High overhead |
A reputation-based trust mechanism for ad hoc networks [50] | Reputation-based trust management algorithm | • Monitors the behavior of neighboring nodes and computing reputation based on monitoring | High computation overhead |
Malicious node detection using fuzzy-based trust level in MANETs [47] | Fuzzy-based trust management | • Certificate authority employs fuzzy-based analyzer to distinguish between trusted and malicious behaviour of nodes by distributing the certificates only to the trusted nodes | More control overhead |
A novel approach for misbehavior detection in ad hoc networks [51] | Fuzzy logic | • System learns the behaviour and applies the fuzzy logic concept for misbehaviour detection | More delay for control packet transmission due to more control packet overhead which effects the data packet transmission |
• Trust parameter is computed for each node which depends on the input parameters | |||
A secure trusted auction-oriented clustering-based routing protocol for MANET [49] | Markov chain analysis of trust model, credit, and reputation scheme | • Effectively detects selfish nodes by credit and reputation scheme to enforce cooperation between nodes | High communication overhead |
Malicious node detection in MANETs: a behavior analysis approach [52] | Trust management | • The approach proposes observing the behavior of mobile nodes depending on different factors | More control overhead |
• Each node in the network can recognize the malicious nodes and prevent them to participate in the communication | |||
AOMDV-based TRIUMF implementation and performance evaluation [53] | Trust management | • The protocol uses an incentive mechanism for selfish node to declare its selfishness behaviour | Unable to detect more than one malicious node in the route |
• It also uses two node-disjoint routes to reduce the malicious searching time |