Mobile ad hoc networks (MANET) are acquiring popularity today, as it offers wireless connectivity to the users irrespective of their geographical position. An ad-hoc network does not have a centralized infrastructure. It is a wireless network where nodes communicate with each other through multiple hops. If the nodes in the ad-hoc network change their positions dynamically, it is called a mobile ad-hoc network (MANET). It has characteristics like shared physical medium, autonomous terminal, limited physical security, infrastructure less communication, Dynamic topology, large degree of freedom, self organizing capability. Such characteristics provide an open environment for users to maintain connectivity irrespective of their geographical positions but, such types of networks are vulnerable to various kinds of attack.
Ad hoc on demand Distance Vector (AODV) is one of the key protocols used for routing in MANET. The security of AODV protocol can be shattered by black hole attack. A Black hole attack can devastate routing in mobile ad hoc network. A Blackhole is a malevolent node that proclaims to have the shortest optimal path to the desired destination node but in reality it does not have any active path to particular destination and the packets received by the black hole from other nodes are dropped. As the black hole attack gives the fake shortest path to the destination hence in our proposed scheme, the first optimal path is discarded and the second optimal route is selected. To maintain data integrity and for prevention of black / gray hole attack hash function is used.
Retrieval of images based on visual features such as color, texture and shape have proven to have it's own set of limitations under different conditions. Various techniques have been implemented using these features like fuzzy color histogram, Tamura texture etc. In this paper we propose a novel method with highly accurate and retrieval efficient approach which will work on large image database with varied contents and background.
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