ARCHITECTURE FOR INTRUSION DETECTION IN MANET in Visual Studio .NET

Generation Code 128 Code Set B in Visual Studio .NET ARCHITECTURE FOR INTRUSION DETECTION IN MANET
54 ARCHITECTURE FOR INTRUSION DETECTION IN MANET
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evidence of malfeasance Another possibility is to require multiple nodes to agree through direct evidence that a node is bad For example, multiple nodes may observe the same malicious behavior through promiscuous monitoring If several nodes agree that a node is bad, it seems reasonable to take advantage of such information when considering the reputation of a node It is still possible that multiple nodes may collude to trick other nodes, but such a case might be more dif cult In the case when the network has many colluding nodes, the MANET may not be able to operate at all This is because a large number of colluding nodes can completely disrupt the basic operations of the network, such as routing, and thereby make it inoperable 5433 Schemes for Stimulating Cooperation An interesting approach for dealing with misbehaving nodes is to provide mechanisms that encourage nodes to be well behaved These techniques not only apply to malicious nodes that seek to disrupt communication, but also to sel sh nodes that do not perform their expected functions as part of the MANET Since a MANET depends on the cooperation of nodes, sel sh behavior is disruptive The techniques discussed here provide incentives for nodes to cooperate and perform their responsibilities Wireless ad hoc networks, as we have seen, depend on every node supporting the various networking functions and other services Performing these additional functions adds to the node s CPU load and drains its battery because of the increased power consumption If every node decides to act sel shly and not participate in the routing process or other required services (including intrusion detection), then the whole MANET breaks down and no communication is possible It is also possible that only a few nodes may decide to act sel shly and stop forwarding packets This will reduce their CPU utilization and battery consumption While the network will still be operating, the overall network performance will not be optimal Buchagge and Boudic [92] have shown that even a small percentage of sel sh nodes (,10 percent) can signi cantly affect the performance of the network Even though this was shown through simulation for a speci c network con guration, intuitively we expect that this will be true in general for a typical network Marti et al [84] show through simulations that, if 10 40 percent of nodes misbehave (by acting sel shly or because of malicious intent), throughput decreases by about 16 32 percent, although nodes near the misbehaving nodes experience much larger decrease of throughput Buttyan and Hubaux [95 97] have proposed schemes using the concept of virtual cash called nuglets The schemes assume that each node has a tamper-resistant hardware module Whenever nodes need to use the network they need to expend some of their virtual cash; the tamper-resistant hardware ensures the integrity of the virtual cash In the Packet Purse Model variation of the scheme, each packet is loaded with nuglets by the source Each forwarding node takes some of the cash loaded in the packet for providing the forwarding service If there are enough nuglets on the packet, the packet will reach the destination Unfortunately with this scheme, the source of the packet needs to know how many hops the packet needs to travel so that it loads the packet with enough cash to satisfy all the forwarding nodes Otherwise the packet may not be forwarded to the destination In a different variation of this scheme called the Packet Trade Model, each packet does not carry cash but is traded by the forwarding nodes for cash Each forwarding node buys the packet for some cash from the previous node and sells it to the next hop for more cash, gaining some cash in the process This model overcomes the limitations of the Packet Purse Model because nodes originating a
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