Extensible, Scalable Monitoring for Clusters of Computers
LISA '97 Proceedings of the 11th USENIX conference on System administration
LISA '98 Proceedings of the 12th USENIX conference on System administration
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Wide Area Network Packet Capture and Analysis
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Design of a Snort-Based Hybrid Intrusion Detection System
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
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Determining how you were attacked is essential to developing a response or countermeasure. Usually, a system or network manager presented with a successful intrusion has very little information with which to work: a possibly corrupted system log, a firewall log, and perhaps some tcpdump output. When hackers come up with a new technique for cracking a network, it often takes the security community a while to determine the method being used. In aviation, an aircraft's "black box" is used to analyze the details of a crash. We believe a similar capability is needed for networks. Being able to quickly learn how an attack works will shorten the effective useful lifetime of the attack. Additionally, the recovered attack records may be helpful in tracking or prosecuting the attacker. Since we've developed a general purpose statistics-gathering system, we believe it will be useful for more than just security. For example, a network manager may desire an historical record of the usage growth of certain applications, or details about the breakdown of types of traffic at different times of day. Such records will provide useful information for network managers in diagnosing performance problems or planning growth. This paper describes an architecture and toolkit for building network traffic analysis and statistical event records: The Network Flight Recorder. The NFR uses a promiscuous packet interface to pass visible traffic into an internally meta-programmed decision engine which routes information about packets and their contents into statistical or logging backends. In addition to packet analysis and collection, the NFR's internal architecture permits network managers to sample interesting portions of network traffic for logging or statistical analysis. The NFR programming language is simple, but powerful enough that you can perform reasonable analysis on traffic before choosing to record it. For example, you might analyze SMTP transactions but only choose to record those relating to a user who is sending spam or abusive E-mail. The analysis language includes a capability for generating alert messages which the rest of the system queues, multiplexes, and delivers. A simplified hyper-query interface allows extensive browsing of the NFR's stored datasets and statistics from any Java-enabled browser. The NFR is currently being deployed at a number of ISPs and commercial sites, and is available for download in source code form from www.nfr.net.