Fast portscan detection using sequential hypothesis testing
International Computer Science Institute · Lawrence Berkeley National Laboratory · +1 more institution
Abstract
Attackers routinely perform random portscans of IP addresses to find vulnerable servers to compromise. Network intrusion detection systems (NIDS) attempt to detect such behavior and flag these portscanners as malicious. An important need in such systems is prompt response: the sooner a NIDS detects malice, the lower the resulting damage. At the same time, a NIDS should not falsely implicate benign remote hosts as malicious. Balancing the goals of promptness and accuracy in detecting malicious scanners is a delicate and difficult task. We develop a connection between this problem and the theory of sequential hypothesis testing and show that one can model accesses to local IP addresses as a random walk on one of…
Citation impact
- FWCI
- 45.33
- Percentile
- 100%
- References
- 9
Authors
4Topics & keywords
- Computer science
- Intrusion detection system
- Server
- Task (project management)
- Random walk
- Host (biology)
- Connection (principal bundle)
- Data mining