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Abstract excerpt: "The experience of the Lawrence Berkeley Laboratory in tracking an intruder suggests that any operating system is insecure when obvious security rules are ignored How a site should respond to an intrusion, whether it is possible to trace an intruder trying to evade detection, what can be learned from tracking an intruder, what methods the intruder used, and the responsiveness of the law enforcement community are also discussed" Significance: Cliff Stoll may have been the first person to understand the importance of network-based security monitoring He documented his 1986 investigation in this paper and the 1989 book The Cuckoo's Egg The following extracts are eerily prescient It's both amazing and disappointing how little has changed since Stoll commented on the state of computer security while he was monitoring German intruders at Lawrence Berkeley Laboratory Highlights: This paper is only 17 pages long, and it is an absolute must-read I could only include a few quotes here, but wanted to share much more Stoll explains why a passive monitoring system, like a network-based full content collection system, is superior to host-based systems in some respects Host-based systems interfere with the systems they watch and they are visible to intruders: "Off-line monitors are invisible even to an intruder with system privileges Moreover, they gave printouts of the intruder's activities on our local area network (LAN), letting us see his attempts to enter other closely linked computers Besides taking up resources, on-line monitors would have warned the intruder that he was being tracked We used this type of off-line monitor and avoided tampering with our operating systems" The author used full content monitoring to perform threat assessment: "Throughout this time, the printouts showed his interests, techniques, successes, and failures We observed the intruder's familiarity with various operating systems and became familiar with his programming style Buried in this chatter were clues to the intruder's location and persona, but we needed to temper inferences based on traffic analysis Only a complete trace back would identify the culprit" In the years since Stoll wrote these words, nothing has changed: "While connected to MILNET, this intruder attempted to enter about 450 omputers, trying to log in using common account names like root, guest, system, or field Taking advantage of well-publicized problems in several operating systems, he was often able to obtain root or system-manager privileges" Network-based monitoring caught activity that disabled host-based monitoring missed Notice how the intruder preferred to appear as though he belonged on his victim systems: "Whenever possible, he disabled accounting and audit trails, so there would be no trace of his presence He planted Trojan horses to passively capture passwords and occasionally created new accounts to guarantee his access into computers Apparently he thought detection less likely if he did not create new accounts, for he seemed to prefer stealing existing, unused accounts".

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When measurements are taken over a period of time, they can form a baseline against which deviations are noted If port 53 UDP traffic typically uses 2% of an organization's bandwidth, an increase to 5% is probably significant (I use a loose definition of "significant" here, not one based in the statistical definition) Deviations from normalcy may or may not represent an intrusion Deviations are indicators, just as session data showing an outbound connection initiated by a Web server is an indicator In this chapter we will use statistical data to gain a better idea of what is happening on our networks, not to trigger any sort of alarm (just as we did not explore alarms in the chapters on full content or session data) When we use any of the three forms of NSM data to trigger an alarm, we enter the realm f alert data, the subject of s 9 and 10 The first set of tools (Cisco accounting through Tcpdstat) provides a snapshot of network activity as it occurs or shortly thereafter These applications are typically used in a reactive manner For example, an administrator who hears that "the network is slow" wants to check for "bandwidth hogs" at that very moment This sort of information can also be used to troubleshoot connectivity to sensors, confirm in-progress denial-of-service attacks, or monitor sessions in near real time These tools are predominantly oriented toward using command lines or terminals The second set of tools (ie, MRTG and Ntop) is used for long-term monitoring or for looking at saved capture files These are best used over periods of days, weeks, or months They can be used to spot trends and collect data for comparison with the current situation.

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