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ABSTRACT
Hostile network traffic is often "different" from benign traffic in ways that can be distinguished without knowing the nature of the attack. We describe a two stage anomaly detection system for identifying suspicious traffic. First, we filter traffic to pass only the packets of most interest, e.g. the first few packets of incoming server requests. Second, we model the most common protocols (IP, TCP, telnet, FTP, SMTP, HTTP) at the packet byte level to flag events (byte values) that have not been observed for a long time. This simple system detects 132 of 185 attacks in the 1999 DARPA IDS evaluation data set [5] with 100 false alarms, after training on one week of attack-free traffic.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Mahoney, M., P. K. Chan, "PHAD: Packet Header Anomaly Detection for Identifying Hostile Network Traffic", Florida Tech. technical report 2001-04, http://cs.fit.edu/~tr/
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Mahoney, M., P. K. Chan, "Learning Models of Network Traffic for Detecting Novel Attacks", Florida Tech. technical report 2002-08, http://cs.fit.edu/~tr/
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Paxson, Vern, "Bro: A System for Detecting Network Intruders in Real-Time", Lawrence Berkeley National Laboratory Proceedings, 7'th USENIX Security Symposium, Jan. 26--29, 1998, San Antonio TX,
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SPADE, Silicon Defense, http://www.silicondefense.com/software/spice/
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