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Rating 3.6 neighbor the clustering information each neighbor maintains and based on that it reorganizes the clusters so that every node is one hop away from every other and propagates the new information throughout the network Whenever a node disappears, its neighbors initiate a similar process for reducing the number of clusters This is a simple algorithm for forming cliques, although it is not very ef cient 54313 Applications of Clustering for Intrusion Detection in MANET The clustering algorithms have been studied extensively for MANET and have been shown to improve the performance of routing and other functions in MANET So a natural question here is whether it is possible to use the clustering concept for organizing the intrusion detection functions ef ciently in a MANET In general that seems to be possible and certain recent publications have suggested this [85, 86] The clustering algorithms used for routing may not be quite applicable directly and might have to be modi ed because of the unique characteristics of the intrusion detection process One potential use of clustering in intrusion detection is for creating a dynamic hierarchy [85] for collecting and consolidating intrusion detection information This would be in lieu of the peer-to-peer architecture that was described in Section 5421 Another potential application of clustering is in distributing the function of collecting evidence in the network For example, the authors of [86] propose the formation of clusters in which a clusterhead is one hop away from every member of the cluster In that case a clusterhead can observe all communications in the cluster through promiscuous monitoring and therefore become the natural chokepoint in the neighborhood for placing the intrusion detection function The clusterhead in this case can then be the single node in the cluster that needs to run the intrusion detection function Such a clusterhead would focus on malicious behavior that can be observed from the network traf c Multiple nodes in the cluster do not need to perform the same function, reducing the power consumption on those nodes The use of clustering algorithms for intrusion detection also has signi cant limitations speci c to intrusion detection The biggest limitation, as remarked earlier, is that these algorithms are prone to attacks themselves since they were not developed with security as a focus They are not resistant to attacks such as clusterheads being taken over by an adversary in order to bypass the intrusion detection mechanism A clusterhead that becomes malicious can introduce malicious intrusion detection reports and share these reports with the rest of the hierarchy This could result in a well-behaved node being declared malicious and being expelled from the network The higher the clusterhead is in the hierarchy, the more severe is the damage caused by a malicious clusterhead The root of the hierarchy can potentially make the whole network inoperable if it becomes malicious. pdf creator software free download windows xp: Free PDF Creator - Download pdf creator software for windows 8.1 PDF Printer for Windows 8.1, PDF Converter for Windows 8.1
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