IETF Logo Mail Archive

Re: [Nmlrg] Machine Learning in network - solicitation for use cases

Sheng Jiang <jiangsheng@huawei.com> Thu, 17 September 2015 06:41 UTC

Return-Path: <jiangsheng@huawei.com>
X-Original-To: nmlrg@ietfa.amsl.com
Delivered-To: nmlrg@ietfa.amsl.com
Received: from localhost (ietfa.amsl.com [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id ABE821ACE20 for <nmlrg@ietfa.amsl.com>; Wed, 16 Sep 2015 23:41:29 -0700 (PDT)
X-Virus-Scanned: amavisd-new at amsl.com
X-Spam-Flag: NO
X-Spam-Score: -3.911
X-Spam-Level:
X-Spam-Status: No, score=-3.911 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, MIME_8BIT_HEADER=0.3, RCVD_IN_DNSWL_MED=-2.3, SPF_PASS=-0.001, T_RP_MATCHES_RCVD=-0.01] autolearn=ham
Received: from mail.ietf.org ([4.31.198.44]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id TZVtVpHLDBCI for <nmlrg@ietfa.amsl.com>; Wed, 16 Sep 2015 23:41:26 -0700 (PDT)
Received: from szxga02-in.huawei.com (szxga02-in.huawei.com [119.145.14.65]) (using TLSv1 with cipher RC4-SHA (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id AED851ACE21 for <nmlrg@irtf.org>; Wed, 16 Sep 2015 23:41:25 -0700 (PDT)
Received: from 172.24.1.50 (EHLO nkgeml403-hub.china.huawei.com) ([172.24.1.50]) by szxrg02-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id CSO01018; Thu, 17 Sep 2015 14:36:56 +0800 (CST)
Received: from NKGEML512-MBX.china.huawei.com ([169.254.7.166]) by nkgeml403-hub.china.huawei.com ([10.98.56.34]) with mapi id 14.03.0235.001; Thu, 17 Sep 2015 14:36:50 +0800
From: Sheng Jiang <jiangsheng@huawei.com>
To: =?utf-8?B?SsOpcsO0bWUgRnJhbsOnb2lz?= <jerome.francois@inria.fr>, "nmlrg@irtf.org" <nmlrg@irtf.org>
Thread-Topic: [Nmlrg] Machine Learning in network - solicitation for use cases
Thread-Index: AdDjmyqcBYGW/oG2RQurcvQ8aGxCogMvPraAACf2tYA=
Date: Thu, 17 Sep 2015 06:36:50 +0000
Message-ID: <5D36713D8A4E7348A7E10DF7437A4B927BB6442C@nkgeml512-mbx.china.huawei.com>
References: <5D36713D8A4E7348A7E10DF7437A4B927BB2962B@nkgeml512-mbx.china.huawei.com> <55F99621.4040409@inria.fr>
In-Reply-To: <55F99621.4040409@inria.fr>
Accept-Language: en-GB, zh-CN, en-US
Content-Language: zh-CN
X-MS-Has-Attach:
X-MS-TNEF-Correlator:
x-originating-ip: [10.111.99.197]
Content-Type: text/plain; charset="utf-8"
Content-Transfer-Encoding: base64
MIME-Version: 1.0
X-CFilter-Loop: Reflected
Archived-At: <http://mailarchive.ietf.org/arch/msg/nmlrg/NTkLSTBHjajC5UC_5wF-QRfQePk>
Subject: Re: [Nmlrg] Machine Learning in network - solicitation for use cases
X-BeenThere: nmlrg@irtf.org
X-Mailman-Version: 2.1.15
Precedence: list
List-Id: Network Machine Learning Research Group <nmlrg.irtf.org>
List-Unsubscribe: <https://www.irtf.org/mailman/options/nmlrg>, <mailto:nmlrg-request@irtf.org?subject=unsubscribe>
List-Archive: <https://mailarchive.ietf.org/arch/browse/nmlrg/>
List-Post: <mailto:nmlrg@irtf.org>
List-Help: <mailto:nmlrg-request@irtf.org?subject=help>
List-Subscribe: <https://www.irtf.org/mailman/listinfo/nmlrg>, <mailto:nmlrg-request@irtf.org?subject=subscribe>
X-List-Received-Date: Thu, 17 Sep 2015 06:41:29 -0000

Hi, Jerome,

Thanks for sharing. It would be helpful if you could introduce a little bit more on how to leverage the machine learning in your use case, such as the learning objects and objectives, etc. It would also useful to discuss the working principle in your use case.

Many thanks and best regards,

Sheng

>-----Original Message-----
>From: nmlrg [mailto:nmlrg-bounces@irtf.org] On Behalf Of Jér?me Fran?ois
>Sent: Thursday, September 17, 2015 12:18 AM
>To: nmlrg@irtf.org
>Subject: Re: [Nmlrg] Machine Learning in network - solicitation for use cases
>
>I have experienced using ML for device fingerprinting meaning that by
>observing traffic pattern (message sequence and timing information) it
>is possible to automatically retrieve the precise types of device (name,
>version, series).
>It is particularily interesting to make network inventory as most of
>cases there are some unknwon devices on the network (user or old ones)
>and finally potentially identifying vulnerable devices from a security
>point of view.
>
>jerome
>
>Le 31/08/2015 05:15, Sheng Jiang a écrit :
>> Hi, all,
>>
>> Thanks for subscribe to NMLRG (Network Machine Learning) mail list. As we
>know, there are already many ongoing researches for Machine Learning in
>network, in many areas. But up to now, there are few matured applications
>yet. So it is the time for a Research Group to work on this future-oriented
>technology.
>>
>> The first step would be to collect possible use cases: where the machine
>learning mechanism could be used in networks. The use cases does not need
>to be mature, but should have potential.
>>
>> Note that this topic is rapidly moving from academic research into practical
>application. Therefore, use cases from university environments, industrial
>research and development organizations are all welcome.
>>
>> Best regards,
>>
>> Sheng
>
>_______________________________________________
>nmlrg mailing list
>nmlrg@irtf.org
>https://www.irtf.org/mailman/listinfo/nmlrg

v2.8.7 | Report a Bug | By Email