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An anomaly is defined as something different, abnormal, peculiar or not easily classified While this concept can be applied to virtually anything, we are interested in how it applies to computer security In this context, an anomaly can be defined as some action or data that is not considered normal for a given system, user or network This definition still covers a fairly wide range and can include such things as traffic patterns, user activity and application behavior The belief is that at least a significant portion of threats or concerning conditions should manifest themselves as anomalies and thus be detectable The general approach used by anomaly detection is that something (ie, a network, a host, a set of users, etc) is observed and compared against expected behavior If variation from the expected is noted, that variation is flagged as an anomaly Often this includes some measure of the scope or nature of the variation and serves to drive further investigation, alerting, and analysis One of the key differences between anomaly detection and other forms of detection is that, rather than defining "what is not allowed or bad," it defines "what is allowed or good" Many traditional forms of detection rely on comparing observed behavior and noting when something known to be "bad" is seen These are often referred to as misuse detection systems, however, this nomenclature can be confusing since anomaly systems also detect misuse A more accurate name, perhaps, is explicit detection systems These systems operate well when the number of possible bad behaviors is small and does not change very rapidly However, in larger systems with greater variation, these two conditions often do not hold It then becomes a very onerous task to maintain the list of what is bad Anomaly detection relies on having some definition of allowed behavior and then noting when observed behaviors differ Often additional information about the deviation is noted including its nature, size and frequency in order to further understand what the anomaly is This operates well when it is easier or more efficient to define what is allowed rather than what is not allowed In these cases, the definition of what is allowed tends to be much shorter It also tends not to require changes as new problems are created or discovered Naturally, however, some problems are more applicable than others to this type of approach In particular, certain considerations may alter the effectiveness of anomaly detection for a specific problem Since it is detecting things in a more general way, an anomaly detection system may not be able to identify a problem as precisely as an explicit system It is also important to consider the space that is being observed for anomalies If it is too large, variant and complex, it may be too difficult to describe problems in a manner general enough to make anomaly detection easible (eg, general human behavior) Fortunately, many computer and network problems tend not to fall into this category which is what makes anomaly detection such an attractive technique Anomaly detection systems monitor networks for two primary criteria, characteristic deviation and statistical deviation While it can certainly be argued that there are more (or less) ways to classify such systems, these two divisions provide a convenient manner in which to discuss the various implementations Characteristic deviations tend to be more qualitative For example, "User joe123 does not normally use transfer files outside of the company" Statistical deviations, on the other hand, tend to be more quantitative For example, "This site's ICMP traffic never exceeds 15 percent of capacity".

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This first principle implies that defensible networks give analysts the opportunity to observe traffic traversing the enterprise's networks The network was designed with monitoring in mind, whether for security or, more likely, performance and health purposes These organizations ensure every critical piece of network infrastructure is accessible and offers a way to see some aspects of the traffic passing through it For example, engineers equip Cisco routers with the appropriate amount of random access memory (RAM) and the necessary version of Internetwork Operating System (IOS) to collect statistics and NetFlow data reflecting the sort of traffic carried by the device Technicians deploy switches with Switched Port ANalyzer (SPAN) access in mind If asymmetric routing is deployed at the network edge, engineers use devices capable of making sense of the mismatched traffic patterns (This is a feature of the new Proventia series of IDS appliances announced by Internet Security Systems, Inc, in late 2003) If the content of encrypted Web sessions must be analyzed, technicians attach IDSs to SSL accelerators that decrypt and reencrypt traffic on the fly A corollary of this principle is that defensible networks can be audited "Accountants" can make records of he "transactions" occurring across and through the enterprise Analysts can scrutinize these records for signs of misuse and intrusion Network administrators can watch for signs of misconfiguration, saturation, or any other problems impeding performance Networks that can be watched can also be baselined to determine what is normal and what is not Technicians investigate deviations from normalcy to identify problems A second corollary is that defensible networks are inventoried If you can watch everything, you should keep a list of what you see The network inventory should account for all hosts, operating systems, services, application versions, and other relevant aspects of maintaining an enterprise network You can't defend what you don't realize you possess.

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