In computer and network security, standard ap- proaches to intrusion detection and response attempt to detect and prevent individual attacks. However, it is not the attack but rather the attacker against which our networks must be defended. To do this, the in- formation that is being provided by intrusion detec- tion systems (IDS) must be gathered and then divided into its component parts such that the activity of in- dividual attackers is made clear. Our approach to this involves the application of Bayesian methods to data being gathered from distributed IDS. With this we hope to improve the capabilities for early detection of dis- tributed attacks against infrastructure and the detec- tion of the preliminary phases of distributed denial of service attacks.
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