| Publisher | USENIX Association | ||
|---|---|---|---|
| Format | HTML & PDF | Date added | 25 Aug 1999 |
| Topics | Artificial Intelligence, Anti-Hacking, Anti-Virus, Network Security | ||
| Downloads | 78 | ||
Current intrusion detection systems lack the ability to generalize from previously observed attacks to detect even slight variations of known attacks. This paper describes new process-based intrusion detection approaches that provide the ability to generalize from previously observed behavior to recognize future unseen behavior. The approach employs artificial neural networks (ANNs), and can be used for both anomaly detection in order to detect novel attacks and misuse detection in order to detect known attacks and even variations of known attacks.
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