Re: open source artificial ignorance-like systems
"Tom Le" <[email protected]>
| Newsgroups | gmane.comp.sysutils.loganalysis |
|---|---|
| Message-ID | <[email protected]> |
On 4/19/07, Stefano Zanero <[email protected]> wrote: > Tom Le wrote: > > The problem with most AI approaches is you have to train the network, > > and in order to do that you have to provide accurate examples (not to > > You seem to think that AI means neural networks: just to let you know, > neural networks are a common instrument in data analysis, and are not > even strictly part of AI anymore... I don't think that at all. I said the problem with most AI approaches (to log analysis) is that it requires training. Unsupervised training can help with feature extraction and anomaly detection if you can provide the proper apriori context with regards to meta data. But if you are talking about AI with regards to security event monitoring, the only way to produce meaningfuł actionable results is with supervised training. > Additionally, you seem to imply here that learning algorithms need to be > supervised (i.e. have pre-labelled samples to train on): this is untrue > as well. I would welcome any examples of SEM for unsupervised training outside of feature extraction techniques which require human intervention to interpret the results anyways. Here the human is the supervisor even if the AI algorithm uses unsupervised training. > > But when you start talking about host based messages or IDS/IPS events, > > it's just impossible to train the network > > Once again, this is your perception, but it does not necessarily > coincide with reality ;) I disagree with you. My reality includes analyzing billions of log events per week in an SEM context. I would appreciate examples of your position. Tom