Nmap Development mailing list archives
Re: Request for Comments: New IPv6 OS detection machine learning engine
From: Varunram Ganesh <vrg2009 () ymail com>
Date: Tue, 21 Feb 2017 04:34:35 +0000 (UTC)
5) As we already thought, having 695 features is quite a lot. Approaches to reduce the amount of features could be for example using neural networks or principal component analysis (PCA). We did play around with such things a bit before, but it might be interesting to have another look. I'm not exactly familiar with these either, but it definitely sounds like it's worth a look!
Unfortunately, me neither. Anyone who is is welcome to apply to the next Google Summer of Code!
I think PCA might be a better choice considering we have a dataset of slightly greater than 300 fingerprints and for neural networks to work correctly, we would need as many fingerprints as features. That being said, as you mentioned, it'd be helpful to have more fingerprints to make the algorithm better (and maybe implement neural networks in the future). Cheers,Varunram
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Current thread:
- Re: Request for Comments: New IPv6 OS detection machine learning engine Mathias Morbitzer (Jan 20)
- Re: Request for Comments: New IPv6 OS detection machine learning engine Fyodor (Feb 09)
- Re: Request for Comments: New IPv6 OS detection machine learning engine Mathias Morbitzer (Feb 20)
- <Possible follow-ups>
- Re: Request for Comments: New IPv6 OS detection machine learning engine Varunram Ganesh (Feb 20)
- Re: Request for Comments: New IPv6 OS detection machine learning engine Mathias Morbitzer (Mar 02)
- Re: Request for Comments: New IPv6 OS detection machine learning engine Fyodor (Feb 09)