Snort mailing list archives

Re: NEED HELP FOR WORK


From: Ghislain Hounmenou via Snort-devel <snort-devel () lists snort org>
Date: Thu, 1 Jun 2023 15:24:50 +0100

Thanks for the feedback!
Thank you very much for your feedback. It is exactly for my master's thesis
that I am doing the work and I have to finish in the next two weeks. I want
you to send me your brief first, and I will read. How are we going to do
the work? Can I already share with you the code of my model that you will
see? And also to see with me how I will do the integration. Thank you.

Le jeu. 1 juin 2023 à 14:33, Hazen Valliant-Saunders <hazenvs () gmail com> a
écrit :

Good Morning Ghislain;

I wrote my Masters on this subject; and consult in this field.

AI / ML is very broad ( since you have a model we'd need to figure out how
to code up the classifier and then run Dev and integration testing on it)
we would have to use the Plugin API / develop a plugin for Snort.

We'd have to work on integrating it as a Plugin for Snort (which is where
we'd need to develop said model / plugin )

I will be happy to help you work on this.

Regards,
Hazen

On Thu, 1 Jun 2023 at 09:26, Ghislain Hounmenou via Snort-devel <
snort-devel () lists snort org> wrote:

Hello everyone, I hope you're doing well. Currently, I'm working on
developing a machine learning plugin for Snort. My idea is to enhance
Snort's capabilities by adding behavior-based (anomaly) detection in
addition to signature-based detection. For this purpose, I trained a
machine learning model using PCA for dimensionality reduction and SVM as
the classifier, using the CICIDS2017 dataset. Now, I would like to know how
I can integrate the trained model into Snort. Are there any existing works
in this direction that can guide me or provide some ideas? I need to
present the solution in two weeks.

Thank you. Regards
--
*Ghislain HOUNMENOU*b
+229 96 418 892 / 64 489 787
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--
Hazen Valliant-Saunders
MSc CISSP CISM CDPSE CMC
IT/IS Consultant
(613) 355-5977



-- 
*Ghislain HOUNMENOU*

Développeur Web
+229 96 418 892 / 64 489 787
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