Mobile ad hoc networks (MANETs) consist of a collection of wireless mobile nodes which dynamically exchange data among themselves without the reliance on a fixed base station or a wired resolution network. MANET nodes are typically well known by their precise power, transformation, and memory effects as well as high degree of mobility. In MANET mobile node is responsible for route establishment using wireless link where each node behave like both as a host and router. In such networks, the wireless mobile nodes may dynamically enter the network as well as go-ahead the network. Mobile ad hoc network is a group of many more devices or nodes with the capability of communication and networking. MANET encounter by number of security threat because of its open entrusted environment with little security settlement, even if security over MANET is not to be enhance up to satisfactory level because of its characteristics Security is an essential service for wired and wireless network communication. Due to its mobility and self routing effective nature, there are many deficiencies in its security. Various security threats show their impact at different layers, Among all of security thread worm hole is consider to be a very serious security thread over MANET. In wormhole two selfish node which is geographically very far away to each other, makes tunnel between each other to cover their actual location and try to believe that they are true neighbors and makes conversation through the wormhole tunnel. Wormhole attacks enable an attacker with limited resources and no cryptographic material to wreak havoc on wireless networks. For wormhole attack to have a best impact on the wired or wireless network, it must fascinate a huge amount of network traffic which is done by giving a shortest route to destination in the network. Therefore, the routes going through the wormhole must be shorter than alternate routes through valid network nodes. This Paper focuses on threat that wormhole attack possesses on network and also mentions few of the initiatives with their respective specifications to solve the problem of wormhole attack.

No abstract

No abstract

In this paper we propose a novel 3D CNN network with localized residual connections for hyperspectral image classification. Our work chalks a comparative study with the existing methods employed for abstracting deeper features and propose a model which incorporates residual features from multiple stages in the network. The proposed architecture processes individual spatiospectral feature rich cubes from hyperspectral images through 3D convolutional layers. The residual connections result in improved performance due to assimilation of both low-level and high-level features. We conduct experiments over Pavia University and Pavia Center dataset for performance analysis. We compare our method with two recent state-of-the-art methods for hyperspectral image classification method. The proposed network outperforms the existing approaches by a good margin.

No abstract