Mobile ad hoc network is a type of self configurable, dynamic wireless network in which all the mobile devices are connected to one another without any centralised infrastructure. Since, the network topology of MANETs changes rapidly. It is vulnerable to routing attacks than any other infrastructure based wireless and wired networks. Hence, providing security to this infrastructure-less network is a major issue. This paper investigates on the security mechanisms that are proposed for Selfish node attack, Shared root node attack and the Control packet attack in MANETs with the aid of a well known multicast routing protocol namely Multicast Ad hoc On Demand Distance Vector (MAODV). The security solutions proposed for each of the above mentioned attacks are evaluated with the help of three evaluation parameters namely packet delivery ratio, control overhead and total overhead. The algorithmic solutions thus obtained are analysed in the simulation environment by using ns-2 simulator

In mobile ad hoc networks, cooperation among active mobile nodes is considered to play a vital role in reliable transmission of data. But, the selfish mobile nodes present in an ad hoc environment refuse to forward neighbouring nodes' packet for conserving its own energy. This intentional selfish behaviour drastically reduces the degree of cooperation maintained between the mobile nodes. Hence, a need arises for devising an effective mechanism which incorporates both energy efficiency and reputation into account for mitigating selfish behaviour in MANETs. In this paper, we propose an Exponential Reliability Coefficient based reputation Mechanism (ERCRM) which isolates the selfish nodes from the routing path based on Exponential Reliability Coefficient (ExRC). This reliability coefficient manipulated through exponential failure rate based on moving average method highlights the most recent past behaviour of the mobile nodes for quantifying its genuineness. From the simulation results, it is evident that, the proposed ERCRM approach outperforms the existing Packet Conservation Monitoring Algorithm (PCMA) and Spilt Half Reliability Coefficient based Mathematical Model (SHRCM) in terms of performance evaluation metrics such as packet delivery ratio, throughput, total overhead and control overhead. Further, this ERCRM mechanism has a successful rate of 28% in isolating the selfish nodes from the routing path. Furthermore, it also aids in framing the exponential threshold point of detection as 0.4, where a maximum number of selfish nodes are identified when compared to the existing models available in the literature. Ó 2015 Production and hosting by Elsevier B.V. on behalf

In mobile ad hoc networks (MANETs), network survivability is considered as a potential factor required for maintaining maximum degree of connectivity among the mobile nodes even during failures and attacks. But, the selfish mobile nodes pose devastating influence towards network survivability. Hence, a prediction model that assesses network survivability through stochastic properties derived from nodes' behaviour becomes essential. This paper proposes a futuristic trust coefficient-based semi-Markov prediction model (FTCSPM) that investigates and quantifies the impact of selfish behaviour towards the survivability of the network. This FTCSPM approach incorporates a non birth-death process for manipulating futuristic trust coefficient since it does not consider the transition of a mobile node from the failed state to a selfish state into account. This semi-Markov prediction model also aids in framing a lower and upper bound for network survivability. Extensive simulations were carried out through ns-2 and the results indicates that FTCSPM show better performance than the existing benchmark mitigation mechanisms like correlated node behaviour model (CNBM), probabilistic behavior model (PBM) and epidemic correlated node behavioural model (ECNBM) proposed for selfish nodes. Further, FTCSPM isolates the selfish nodes rapidly at the rate of 33 % than the considered benchmark systems. Furthermore, the validation of this prediction model performed through Weibull distribution has a high degree of correlation with the simulation results and thus assures the reliability and correctness of the proposed approach. In addition, this approach computes the mean transition time incurred by a mobile node to transit from cooperative to selfish mode as 6.49 s and also identifies the minimum and maximum selfish behaviour detection time as 140 and 180 s, respectively.

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