"0139-570X" . "Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purpose Intrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However these techniques are less successful when attack characteristics vary from built in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define normal and abnormal behaviour of a system. Also for building anomaly sys" . "2"^^ . "2"^^ . "5"^^ . . . "Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purpose Intrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However these techniques are less successful when attack characteristics vary from built in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define normal and abnormal behaviour of a system. Also for building anomaly sys"@en . "Zem\u011Bd\u011Blsk\u00E1 ekonomika" . . "Neural networks in intrusion detection systems" . . "intrusion detection system (IDS), misuse IDS, anomaly IDS, Kohonen\u00B4s self-organizing maps"@en . . "1" . "Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purpose Intrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However these techniques are less successful when attack characteristics vary from built in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define normal and abnormal behaviour of a system. Also for building anomaly sys"@cs . . . "Neural networks in intrusion detection systems"@en . "35;39" . . "[49E1FC8A11CF]" . . "Brechlerov\u00E1, Dagmar" . . . . "Neuronov\u00E9 s\u00EDt\u011B v syst\u00E9mech pro detekci napaden\u00ED"@cs . . "Neural networks in intrusion detection systems" . "Vesel\u00FD, Arno\u0161t" . "50" . . "RIV/60460709:41110/04:5038" . "575938" . . "41110" . "Neuronov\u00E9 s\u00EDt\u011B v syst\u00E9mech pro detekci napaden\u00ED"@cs . "CZ - \u010Cesk\u00E1 republika" . . "RIV/60460709:41110/04:5038!RIV/2005/MSM/411105/N" . "Neural networks in intrusion detection systems"@en . . "Z(MSM 411100010)" .