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Protection of an intrusion detection engine with watermarking in ad hoc networks
Mobile ad hoc networks have received great attention in recent years, mainly due to the evolution of wireless networking and mobile computing hardware. Nevertheless, many inherent vulnerabilities exist in mobile ad hoc networks and their applications that affect the security of wireless transactions. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient we need a second line of defense, Intrusion Detection. In this pa-per we present an intrusion detection engine based on neural networks and a protection method based on watermarking techniques. In particular, we exploit information visualization and machine learning techniques in order to achieve intrusion detection and we authenticate the maps produced by the application of the intelligent techniques using a novel combined watermarking embedding method. The performance of the proposed model is evaluated under different traffic conditions, mobility patterns and visualization metrics
Observation-based Cooperation Enforcement in Ad Hoc Networks
Ad hoc networks rely on the cooperation of the nodes participating in the
network to forward packets for each other. A node may decide not to cooperate
to save its resources while still using the network to relay its traffic. If
too many nodes exhibit this behavior, network performance degrades and
cooperating nodes may find themselves unfairly loaded. Most previous efforts to
counter this behavior have relied on further cooperation between nodes to
exchange reputation information about other nodes. If a node observes another
node not participating correctly, it reports this observation to other nodes
who then take action to avoid being affected and potentially punish the bad
node by refusing to forward its traffic. Unfortunately, such second-hand
reputation information is subject to false accusations and requires maintaining
trust relationships with other nodes. The objective of OCEAN is to avoid this
trust-management machinery and see how far we can get simply by using direct
first-hand observations of other nodes' behavior. We find that, in many
scenarios, OCEAN can do as well as, or even better than, schemes requiring
second-hand reputation exchanges. This encouraging result could possibly help
obviate solutions requiring trust-management for some contexts.Comment: 10 pages, 7 figure
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