Biblio

A Mobile Ad Hoc Network (MANET) is considered a type of network which is wireless and has no fixed infrastructure composed of a set if nodes in self organized fashion which are randomly, frequently and unpredictably mobile. MANETs can be applied in both military and civil environments ones because of its numerous applications. This is due to their special characteristics and self-configuration capability. This is due to its dynamic nature, lack of fixed infrastructure, and the no need of being centrally managed; a special type of routing protocols such as Anonymous routing protocols are needed to hide the identifiable information of communicating parties, while preserving the communication secrecy. This paper provides an examination of a comprehensive list of anonymous routing protocols in MANET, focusing their security and performance capabilities.

Mobile Ad hoc Networks (MANETs) are wireless networks that are void of fixed infrastructure as the communication between nodes are dependent on the liaison of each node in the network. The efficacy of MANET in critical scenarios like battlefield communications, natural disaster require new security strategies and policies to guarantee the integrity of nodes in the network. Due to the inherent frailty of MANETs, new security measures need to be developed to defend them. Intrusion Detection strategy used in wired networks are unbefitting for wireless networks due to reasons not limited to resource constraints of participating nodes and nature of communication. Nodes in MANET utilize multi hop communication to forward packets and this result in consumption of resources like battery and memory. The intruder or cheat nodes decide to cooperate or non-cooperate with other nodes. The cheat nodes reduce the overall effectiveness of network communications such as reduced packet delivery ratio and sometimes increase the congestion of the network by forwarding the packet to wrong destination and causing packets to take more times to reach the appropriate final destination. In this paper a decision tree based artificial immune system (AIS) strategy is utilized to detect such cheat nodes thereby improving the efficiency of packet delivery.

Mobile Ad-hoc Networks (MANETs) have gained popularity both in research and in industrial fields. This is due to their ad hoc nature, easy deployment thanks to the lack of fixed infrastructure, self-organization of its components, dynamic topologies and the absence of any central authority for routing. However, MANETs suffer from several vulnerabilities such as battery power, limited memory space, and physical protection of network nodes. In addition, MANETs are sensitive to various attacks that threaten network security like Blackhole attack in its different implementation (single and multiple). In this article, we present the simulation results of single and multiple Blackhole attack in AODV and OLSR protocols on using NS-3.27 simulator. In this simulation, we took into consideration the density of the network described by the number of nodes included in the network, the speed of the nodes, the mobility model and even we chose the IEEE 802.11ac protocol for the pbysicallayer, in order to have a simulation, which deals with more general and more real scenarios. To be able to evaluate the impact of the attack on the network, the Packet delivery rate, Routing overhead, Throughput and Average End to End delay have been chosen as metrics for performance evaluation.

For sharing resources using ad hoc communication MANET are quite effective and scalable medium. MANET is a distributed, decentralized, dynamic network with no fixed infrastructure, which are self- organized and self-managed. Achieving high security level is a major challenge in case of MANET. Layered architecture is one of the ways for handling security challenges, which enables collection and analysis of data from different security dimensions. This work proposes a novel multi-layered outlier detection algorithm using hierarchical similarity metric with hierarchical categorized data. Network performance with and without the presence of outlier is evaluated for different quality-of-service parameters like percentage of APDR and AT for small (100 to 200 nodes), medium (200 to 1000 nodes) and large (1000 to 3000 nodes) scale networks. For a network with and without outliers minimum improvements observed are 9.1 % and 0.61 % for APDR and AT respectively while the maximum improvements of 22.1 % and 104.1 %.