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Rate of Routing Updates a node may attempt to send routing updates much more often than required by the routing protocol This may cause instability in the routes, and may drain other nodes batteries and CPU since the nodes have to process all those updates Routing updates are usually caused by, for example, node movements, changes in link connectivity, new nodes joining the network, or nodes disappearing from the network Given a speci c application or mission if there is a reasonable level of understanding of the frequency of these events then it may be possible to determine the expected rate of routing changes for nodes If a speci c node is generating routing updates and changes that signi cantly exceed that rate, it is often an indication of an attack It is of course possible for this technique to generate false positives because the routing changes may be generated for valid reasons For example, in a battle eld environment, sudden movements may be experienced due to sudden unexpected events As remarked earlier, there is always a trade-off between setting a threshold to such a small level that several false positives are generated and setting a threshold to a large value that may allow attacks to go undetected Number of Neighbors a node may advertise a large number of nodes as its neighbors As discussed earlier this type of an attack may create a black hole It may be possible to detect that attack if the number of nodes advertised is abnormally high for the density of the network This can be especially true if the neighbors of the offending node advertise only a small number of neighbors Again, it is possible to get false positives because node positions may actually justify signi cant discrepancies in the number of neighbors This property is actually an example of the usage of emergent properties [103] An emergent algorithm leverages the features that no individual node can provide, but that emerge through the collaboration of many nodes Thus the set of neighbors is one such example of an emergent property Length of Routes this applies to routing protocols that advertise complete routes such as DSR An attacker may try to insert incorrect routes to cause network instabilities this way Based on the expected connectivity of the network, changes in routes and their length may help detect attackers when there is a signi cant variation from expected behavior.



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Two functions in the default package help with RL encoding: escape() and unescape(). These convert strings to and from their URL-encoded versions. string: Control qr bidimensional barcode size for .var vars: URLVariables = new URLVariables(); vars.make = "Panasonic"; vars odel = "PT-AE2000U"; vars.resolution = "1080p"; trace(vars.toString()); //make=Panasonic&model=PT%.Related: Print EAN-13 .NET , .NET EAN 128 Generator , UPC-A Generator .NET

This chapter describes two statistical anomaly detection techniques for cyber attack detection: the EWMA (Exponentially Weighted Moving Average) control chart which is a univariate Statistical Process Control (SPC) technique, and the Chi-Square Distance Monitoring method (CSDM) which is a multivariate SPC technique Many SPC techniques [1 2] have traditionally been developed and applied to monitor the quality of manufacturing processes SPC techniques rst build the statistical model of the process data obtained from an in-control process to contain only random variations of the process data SPC considers the process out of control with an assignable cause other than random causes of data variations if the process data shows a statistically signi cant deviation from the statistical in-control data model Consider that a computer and network system is in control if there are only normal use activities, but is out-of-control if there are also attack activities This makes the anomaly detection methodology for cyber attack detection similar to SPC techniques [3] in rst building the norm or in-control pro le of the process data and then using the norm pro le to detect a large deviation as anomaly or out-ofcontrol caused by an attack This chapter presents the application of a nivariate SPC technique, the EWMA control chart, and a multivariate SPC technique, CSDM, to cyber attack detection. Code Encoder In .NET Using Barcode printer for .Related: 

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