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exploit the limitations of promiscuous monitoring for evading detection Allowing nodes to compare their observations also reduces false alarms because multiple nodes will compare their view of the suspicious node s behavior Sterne et al [85] describes such a scheme where reports from nodes monitoring their neighbors promiscuously are propagated and consolidated throughout the intrusion detection hierarchy This results in much more precise intrusion detection with fewer false positives However, this also causes increased communication overheads Anjum and Talpade [102] have proposed a technique that overcomes the limitations of promiscuous monitoring altogether That technique is called LiPaD (lightweight packet drop detection for ad hoc networks) In this scheme, every node keeps track of each ow that is either originating or terminating, or passing through that node A ow is de ned by the source and destination IP address tuple in the IP header For each such ow, the node keeps track of the packets the node sends and receives Periodically, every node reports ow statistics to a coordinator that combines those statistics The coordinator can then run detection algorithms that take advantage of the exact and actual information about the number of packets each node is forwarding This is instead of the indirect information based on promiscuous monitoring The coordinator examines all the data provided by every node and looks for ows where a node is not forwarding as many packets as expected This can be achieved because the coordinator has knowledge about the number of packets forwarded by each hop Figure 511 shows one simple such example In this case, a ow originates on node A and is destined for node D Packets for this ow are routed through nodes B and C Each node that is part of the ow (in this case nodes A, B, C, and D), report periodically (let us say every 5 s) to the coordinator (node E) the number of packets they received and transmitted for this ow Node A will only report the packets originating from it (the ow is assumed to be unidirectional), node B will report the number of packets it received from node A and the number of packets it forwarded to node C, and so on The coordinator plays a key role in this architecture because it is the one that correlates the statistics provided by the other nodes Anjum and Talpade [102] conclude that a single coordinator can handle potentially a few hundred nodes Larger networks would need multiple coordinators This scheme has also been shown to work even if some of the nodes are lying (in their reports to the coordinator) For example, let us assume node C in Figure 511 received 20 packets but only forwarded 15 It will either need to report to the coordinator that it.

The same goes for the remote interface, which only includes one method:

y1[i] = g(t; y2[i], y3[i], ) (i = 1, 2, , n)

package jswc04a;

import javaxejb*; import javarmiRemoteException; /** * This is the Remote Interface for the Stateless Session EJB * <tt>OutletServicesSL</tt> * * @see jswc04aOutletServicesSLHome * @see jswc04aOutletServicesSLBean */ public interface OutletServicesSL extends EJBObject { /** * This method assigns an outlet to an order * The assignment is based on the postal code and city * @param orderNum the order identifier * Oreturns the outlet identifier assigned to the order */ public long assignOutlet(long orderNum) throws RemoteException, P2GException; }

(3-2b)

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The actual implementation of the bean is responsible for assigning an outlet to an order The EJB method replaces the stored procedure assignOutlet It is interesting to note the fact that this bean does not update the database This continues to be the responsibility of the OrderMaintenanceS servlet, which updates the database with the values provided by this bean

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The simulation time variable is t g() stands for any expression that can be used in a scalar assignment Such a vector expression may involve literal numbers, scalar parameters, parentheses, library functions, user-defined functions, or table-lookup functions An error is returned when one tries to combine vectors with unequal dimensions For example, if y, u, v, and z are n-dimensional vectors, then

In a fully developed system, however, servlets would not usually update the database This would be the responsibility of the entity bean, which will be covered more fully in 5

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