Re: [Idnet] Intelligence-Defined Network Architecture and Call for Interests

Brian Njenga <iambrianmuhia@gmail.com> Tue, 28 March 2017 18:38 UTC

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From: Brian Njenga <iambrianmuhia@gmail.com>
Date: Tue, 28 Mar 2017 18:38:20 +0000
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To: Jérôme François <jerome.francois@inria.fr>, Oscar Mauricio Caicedo Rendon <omcaicedo@unicauca.edu.co>, Sheng Jiang <jiangsheng@huawei.com>
Cc: "idnet@ietf.org" <idnet@ietf.org>
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Subject: Re: [Idnet] Intelligence-Defined Network Architecture and Call for Interests
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Got it, thanks! Great response. What other research questions do people
have?

On Tue, 28 Mar 2017, 21:26 Jérôme François, <jerome.francois@inria.fr>
wrote:

> Hi,
>
>
> Le 28/03/2017 à 20:06, Brian Njenga a écrit :
>
> I'm glad that the discussions​ on how to make AI/ML useful in the design
> of the internet's architecture are continuing, albeit under a different
> name. I'd like to participate remotely as well.
>
> I have a question that someone more thoughtful​ than I could answer: Are
> there research questions on how to anticipate network-threatening DDOS
> attacks, such as those coming from the Mirai botnet family, using ML? Even
> going as far as designing and standardising an efficient, secure network
> protocol for IoT devices. This is a complicated issue, which involves
> emerging markets, so I'm interested in useful ideas from any angle.
>
> Regarding DDoS, I think we have to consider two angles even when
> considering protecting the network. The flooding-like attacks (1) and the
> most sophisticated attack that can highly degrade service performance even
> with few packets (2) (and of course this also concerns network service,
> even more than before with network softwarization which puts network
> functions into VM, being thus more exposed than before in my opinion).
>
> For type 1, there are usually observable signs of a future attack (without
> ML) in the hours or days before with an increasing load. However even if
> you observe it, it is very hard to fully characterize it and so prevent it
> to really happen. For type 2, you basically need to predict what should be
> the load induced by a packet or flow when considering the targeted service.
> Assuming you have no complete knwoledge of the service, you can try to use
> some learning and regression techniques to do it but assuming also that the
> trafic is encrypted, the problem becomes more difficult.
>
> jerome
>
>
> Thanks, and I'm glad to meet you all.
>
> Best regards,
> Brian Muhia.
>
> On Tue, 28 Mar 2017, 20:02 Oscar Mauricio Caicedo Rendon, <
> omcaicedo@unicauca.edu.co> wrote:
>
> Hi, all,
>
> If there is a meeting, I would like to participate remotely.
>
> Best regards,
>
> Oscar
>
> On Tue, Mar 28, 2017 at 11:29 AM, Sheng Jiang <jiangsheng@huawei.com>
> wrote:
>
> Hi, all,
>
> Although there are many understanding for Intelligence-Defined Network, we
> are actually using this IDN as a term reference to the SDN-beyond
> architecture that we presented in IETF97, see the below link. A reference
> model is presented in page 3, while potential standardization works is
> presented in page 9.
>
>
> https://www.ietf.org/proceedings/97/slides/slides-97-nmlrg-intelligence-defined-network-01.pdf
>
> Although it might be a little bit too early for AI/ML in network giving
> the recent story of the concluded proposed NMLRG, we still would like to
> call for interests in IDN. Anybody (on site in Chicago this week) are
> interested in this or even wider topics regarding to AI/ML in network,
> please contact me on jiangsheng@huawei.com . Then we may have an informal
> meeting to discuss some common interests and potential future activities
> (not any activities in IETF, but also other STO or experimental trails,
> etc.)  on Thursday morning.
>
> FYI, we have already working on a Work Item, called IDN in the ETSI NGP
> (Next Generation Protocol) ISG, links below.
>
> https://portal.etsi.org/tb.aspx?tbid=844&SubTB=844
> https://portal.etsi.org/webapp/WorkProgram/Report_WorkItem.asp?WKI_ID=51011
>
> Meanwhile, please do use this mail list as a forum to discuss any topics
> that may applying AI/ML into network area.
>
> Best regards,
>
> Sheng
> _______________________________________________
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>
>
>
>
> --
> *Oscar Mauricio Caicedo Rendón*
> *PhD Computer Science - Federal University of Rio Grande do Sul*
> *Full Profesor - University of Cauca*
>
> ------------------------------
> * Universidad del Cauca: Comprometidos con la calidad. *
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> --
> Some say he really tries to learn efficiently.
>
>
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>
> --
Some say he really tries to learn efficiently.