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When IDSs were first contemplated in the 1970s and 1980s, many focused on anomaly detection Researchers continue to devote energy to this method, but pattern-based detection has been the dominant strategy for the last decade Pattern-based detection prevailed for a few simple reasons First, it was easier for developers to implement Searching a packet or reassembled stream for a string of characters is conceptually simple Ever-increasing traffic loads and deployment of encryption frustrate this approach, but pattern matching survives Second, it is easier for analysts to understand If an analyst knows the detection product is watching for a certain pattern, it makes sense when the IDS reports seeing that pattern If the pattern does not indicate a malicious event occurred, it's not the IDS's fault Verification has been lacking, but NSM approaches and integration of assessment techniques make pattern matching increasingly effective Third, it is much easier to deploy a rule based on a new pattern than it is to implement a new algorithm for anomaly-based intrusion detection Snort rules are released within hours of the discovery of a new worm, exploit, and other malicious code Engineers and analysts can plug the new rule into their product and validate or tune it as necessary Anomaly detection is not dead, however Pattern-matching systems are frequently compared to signature-based antivirus products If an antivirus product strictly relied n patterns to intercept and defeat malware, users would suffer infections much more often Antivirus products supplement their pattern-matching features with heuristic detection algorithms Heuristic techniques concentrate more on the acts the malware take, like opening network sockets, sending e-mail, and so on, and less on the code used to bring these acts to life Implementing heuristic detection or anomaly-based detection requires knowing what is normal, suspicious, and malicious We encountered those terms earlier in the book with respect to manual inspection of security events In some sense a human analyst is an anomaly detection device An experienced human analyst develops a sense of what is normal for the organizations he or she monitors Seeing an alert or session that falls outside those boundaries of normality prompts the analyst to investigate Validating these unusual events requires access to high-fidelity network traffic, as is provided by session data and full content data Network profiling is related to anomaly detection It's the idea that organizations should develop a formal sense of the devices and traffic patterns required for normal operational use Introduction of new devices or traffic types should raise an alarm Marcus Ranum calls this technique first seen anomaly detection: "[A first seen anomaly detection] system treats the first time it sees an instance of a thing as an anomaly It's accurate that something never seen before is always anomalous, in at least a few senses of the word When I was looking at statistical anomaly detection for IDS I realized that the first seen anomaly was 99% of what you'd get [with statistical anomaly detection products]".

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We now appreciate that NSM is concerned with I&W According to the NSM definition, indicators are collected and analyzed, and warnings are escalated In the NSM world, distinct components are responsible for these actions Products perform collection A product is a piece of software or an appliance whose purpose is to analyze packets on the network Products are needed on high-speed networks because people cannot interpret traffic without assistance I discuss numerous NSM products in Part II of this book People perform analysis While products can form conclusions about the traffic they see, people are required to provide context Acquiring context requires placing the output of the product in the proper perspective, given the nature of the environment in which the product operates Because few products are perfectly customized for the networks they monitor, people increasingly complement deficiencies in software This is not the fault of the developer, who cannot possibly code his product to meet all f the diverse needs of potential customers On the other hand, it is an endorsement of open source software Being free to accept modifications by end users, open source software is best suited for customization Just as products must be tuned for the local environment, people must be trained to understand the information generated by their products Part IV gives suggestions for training analysts Processes guide escalation Escalation is the act of bringing information to the attention of decision makers Decision makers are people who have the authority, responsibility, and capability to respond to potential incidents Without escalation, detection is virtually worthless Why detect events if no one is responsible for response .

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It seems the number of disgruntled IDS owners exceeds the number of satisfied customers Why are IDS deployments prone to failure The answer lies in the comparison among "must-have" products of the 1990s The must-have security product of the mid-1990s was the firewall A properly configured firewall implements access control (ie, the limitation of access to systems and services based on a security policy) Once deployed, a firewall provides a minimal level of protection If told to block traffic from the Internet to port 111 TCP, no one need ever check that it is doing its job (The only exception involves unauthorized parties changing the firewall's access control rules) This is a technical manager's dream: buy the box, turn the right knobs, and push it out the door It does its job with a minimum amount of attention After the firewall, security managers learned of IDSs In the late 1990s the IDS became the must-have product Commercial vendors ike Internet Security Systems, the Wheel Group (acquired by Cisco in February 1998), and Axent (acquired by Symantec in July 2000) were selling IDS software by fall 1997 Articles like those in a September 1997 issue of InternetWeek praised IDSs as a "layer of defense that goes beyond the firewall" Even the Gartner Group, now critical of intrusion detection products, was swept up in the excitement In that InternetWeek article, the following opinion appeared:. ABC Amber CHM Converter Trial version, http://wwwprocesstextcom WBR>abcchmhtml in .NET Drawer QR Code. 128 In C#.NET Using Barcode maker for Visual .Related: Print Code 128 C# , UPC-A Generation Excel , Print Code 128 ASP.NET

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Of all the sources of NSM information, session data is the most useful Session data quickly reduces millions of packets to summaries of conversations or flows These conversations show who talked to whom, when, using what ports and protocols, for how long, and how much data was passed during the session The content of the session is not captured unless full content monitoring is performed on one or more packets of the session Session data is the incident responder's best friend because it answers three out of the four most pressing questions a decision maker faces Can ou guess which one session data cannot answer 1 2 3 4 Are one or more servers definitely compromised If one or more servers are compromised, what did we lose Where else did the intruder go Is the intruder back today . ABC Amber CHM Converter Trial version, http /wwwprocesstextcom/. 13 In Visual Studio .NET Using Barcode recognizer for .Related: Print ISBN Excel , Print ISBN VB.NET , C# Interleaved 2 of 5 Generating

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