Re: [Idnet] A few ideas/suggestions to get us going
Adeel Rehman <adeelrehman85@gmail.com> Thu, 23 March 2017 18:00 UTC
Return-Path: <adeelrehman85@gmail.com>
X-Original-To: idnet@ietfa.amsl.com
Delivered-To: idnet@ietfa.amsl.com
Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id A4665129AEB for <idnet@ietfa.amsl.com>; Thu, 23 Mar 2017 11:00:43 -0700 (PDT)
X-Virus-Scanned: amavisd-new at amsl.com
X-Spam-Flag: NO
X-Spam-Score: -1.748
X-Spam-Level:
X-Spam-Status: No, score=-1.748 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, FREEMAIL_ENVFROM_END_DIGIT=0.25, FREEMAIL_FROM=0.001, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_NONE=-0.0001, SPF_PASS=-0.001, URIBL_BLOCKED=0.001] autolearn=no autolearn_force=no
Authentication-Results: ietfa.amsl.com (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com
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 ITqezoX3sL_m for <idnet@ietfa.amsl.com>; Thu, 23 Mar 2017 11:00:40 -0700 (PDT)
Received: from mail-qt0-x233.google.com (mail-qt0-x233.google.com [IPv6:2607:f8b0:400d:c0d::233]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 713A21294B8 for <idnet@ietf.org>; Thu, 23 Mar 2017 11:00:40 -0700 (PDT)
Received: by mail-qt0-x233.google.com with SMTP id x35so182083251qtc.2 for <idnet@ietf.org>; Thu, 23 Mar 2017 11:00:40 -0700 (PDT)
DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=mime-version:in-reply-to:references:from:date:message-id:subject:to; bh=WIUTdJHGXEO/W482r43DsE2iwyEay+/jeEOPj1ZC0MM=; b=cxl75nZn+UwR5UBee6DUnFrsq4fmphcr0eXabnZJ+dmgXd8UbxBvG/CK/Bd914ZNTT 6ddXcA8XijUjNRf253U/KJ40ONrRmVFFWnOUwFLISZqDRfcPgqNcIdbpr2FxuHathtdq J+kNqurdiZQOe2bgsw9P/2hxgg1R29uwfFFSPFHtPdz7fnk81xLmpaWjVJ6LV6tyGOxk QlBe5b7t39UZC9fc4ldGj/eJjpkoEWia05zuqWT1UZ9GvpKeK6brOekdGpIEp/rIAB8p WBueeiz4zCCMdEDlwPPP+JT1/DOVj+vVnKGV7Mo3Te23m1rP7/GI08NqBRd2+Bnqcdwx GUNQ==
X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:mime-version:in-reply-to:references:from:date :message-id:subject:to; bh=WIUTdJHGXEO/W482r43DsE2iwyEay+/jeEOPj1ZC0MM=; b=NSYj5KyJj11vz00K74zG60kHsT+xSXLYle8XuUwWQzeVIr1M+ySB8uMxCCyBeW2cEq Umbpnrwj1REuSF9V1qVAUFZfBB/BlWuSObdpMhvK47LeJQiV7X1m+7SKvOIahT3rM/Nb KwiF6PVLlKT4wWzFdzyV3yvM8NJYn9jcjDOxUoHuBLcCs6BtnWfyao8nhl3zqVs4sCnl J5zvOoXEFU2IC9PPaqg3UQ/1WdEBlVGAgNzl7AqF6plWTBny7qDHXH6cqY+PNroBel2S AtBrhD8RQlggzPGwqHpwwHWXHvI1mhhtU/2Ghp64E1gduiEqdxhNaH7gEHbHbKL1Oh89 n4KQ==
X-Gm-Message-State: AFeK/H0wj3//OGgXrkoRs6wK7yUD1LY4VpB6UTAT/xL3OukCaRvj7VXxbe1XHa4kps1s6HGr+gthB/guqShEHg==
X-Received: by 10.237.37.71 with SMTP id w7mr3497413qtc.34.1490292039362; Thu, 23 Mar 2017 11:00:39 -0700 (PDT)
MIME-Version: 1.0
Received: by 10.237.52.196 with HTTP; Thu, 23 Mar 2017 11:00:38 -0700 (PDT)
In-Reply-To: <CAN5YCF2xERjvHtkv18XK3Wvmi6WwumHzk1iW0zktvZ9_3WTONQ@mail.gmail.com>
References: <CAHiKxWh26ciY-Pf78EH3CLO1+d3utikMr1N8GwKWJzkZQAAu9g@mail.gmail.com> <CAN5YCF2xERjvHtkv18XK3Wvmi6WwumHzk1iW0zktvZ9_3WTONQ@mail.gmail.com>
From: Adeel Rehman <adeelrehman85@gmail.com>
Date: Thu, 23 Mar 2017 14:00:38 -0400
Message-ID: <CAN5YCF0eeAS2N250+AS4Sm+xfZuzjVd9Xe6Dn5OrUBbhe3zLjQ@mail.gmail.com>
To: David Meyer <dmm@1-4-5.net>, idnet@ietf.org
Content-Type: multipart/alternative; boundary="001a114203d69e351f054b69a763"
Archived-At: <https://mailarchive.ietf.org/arch/msg/idnet/y3ynRG5MrZ4dJHFxy16V1IgqZqI>
Subject: Re: [Idnet] A few ideas/suggestions to get us going
X-BeenThere: idnet@ietf.org
X-Mailman-Version: 2.1.22
Precedence: list
List-Id: "The IDNet \(Intelligence-Defined Network\) " <idnet.ietf.org>
List-Unsubscribe: <https://www.ietf.org/mailman/options/idnet>, <mailto:idnet-request@ietf.org?subject=unsubscribe>
List-Archive: <https://mailarchive.ietf.org/arch/browse/idnet/>
List-Post: <mailto:idnet@ietf.org>
List-Help: <mailto:idnet-request@ietf.org?subject=help>
List-Subscribe: <https://www.ietf.org/mailman/listinfo/idnet>, <mailto:idnet-request@ietf.org?subject=subscribe>
X-List-Received-Date: Thu, 23 Mar 2017 18:00:43 -0000
Thank you David for your feedback :) Sorry i forgot to include distro initially. On Thu, Mar 23, 2017 at 1:40 PM, Adeel Rehman <adeelrehman85@gmail.com> wrote: > Hi David > > > > You have point out excellent shortcomings of Machine learning applications > in Networking field. I have been chasing the same question for a while now. > > > I think part of the reason Network Packet data is very well > structured/designed as compare to other data sources (image, text etc). The > network data can be exploited using domain based algorithms very > effectively. Applying ML algorithm to learn the rules of network traffic is > somewhat costly compare to domain based algorithm. For e.g. > > > a. Learning shortest path, we have Dijkstra algorithm. Do we need > ML for this? > > > b. TCP optimization. We have 3 or 4 Optimization algorithms that are > very cost effective, run in client and server stack. Do we need ML for this? > > > c. There are ML papers that show HTTPS classification with good > accuracy using SVM, and Decision tree algorithms. But do we need these > algorithms? We can get classification using SSL SNI packet during SSL > handshake and that would be 100% accurate. > > Having said that I think there are areas where Machine learning can be > really helpful in detection non-structured behavior in Network Traffic > > a. Anomaly Detection and Threat prevention. There are several > algorithms out there but I think ML algorithms can outperform in this area. > I know one security vendor effectively uses ML to prevent DDOS attacks. > > b. Subscriber behavior, this is a hot topic for Telco operators. I > think unsupervised topic modeling ML method can provide grouping of > subscribers based on their usage. I actually have not seen any > vendor/operator doing it currently, may be my knowledge is limited. > > c. Self-orchestrated Network, this can be a big thing with NFV and > Cloud applications. ML algorithms can play a vital part here. I see Cognet > 5GPPP is taking initiative on this, but not much work from other vendors. > > and i apolo > > On Wed, Mar 22, 2017 at 1:29 PM, David Meyer <dmm@1-4-5.net> wrote: > >> Folks, >> >> I thought I'd try to get some discussion going by outlining some of my >> views as to why networking is lagging other areas in the development and >> application of Machine Learning (ML). In particular, networking is way >> behind what we might call the "perceptual tasks" (vision, NLP, robotics, >> etc) as well as other areas (medicine, finance, ...). The attached slide >> from one of my decks tries to summarize the situation, but I'll give a bit >> of an outline below. >> >> So why is networking lagging many other fields when it comes to the >> application of machine learning? There are several reasons which I'll try >> to outline here (I was fortunate enough to discuss this with the >> packetpushers crew a few weeks ago, see [0]). These are in no particular >> order. >> >> First, we don't have a "useful" theory of networking (UTON). One way to >> think about what such a theory would look like is by analogy to what we see >> with the success of convolutional neural networks (CNNs) not only for >> vision but now for many other tasks. In that case there is a theory of how >> vision works, built up from concepts like receptive fields, shared weights, >> simple and complex cells, etc. For example, the input layer of a CNN isn't >> fully connected; rather connections reflect the receptive field of the >> input layer, which is in a way that is "inspired" by biological vision >> (being very careful with "biological inspiration"). Same with the >> alternation of convolutional and pooling layers; these loosely model the >> alternation of simple and complex cells in the primary visual cortex (V1), >> the secondary visual cortex(V2) and the Brodmann area (V3). BTW, such a >> theory seems to be required for transfer learning [1], which we'll need if >> we don't want every network to be analyzed in an ad-hoc, one-off style >> (like we see today). >> >> The second thing that we need to think about is publicly available >> standardized data sets. Examples here include MNIST, ImageNet, and many >> others. The result of having these data sets has been the steady ratcheting >> down of error rates on tasks such as object and scene recognition, NLP, and >> others to super-human levels. Suffice it to say we have nothing like these >> data sets for networking. Networking data sets today are largely >> proprietary, and because there is no UTON, there is no real way to compare >> results between them. >> >> Third, there is a large skill set gap. Network engineers (us!) typically >> don't have the mathematical background required to build effective machine >> learning at scale. See [2] for an outline of some of the mathematical >> skills that are essential for effective ML. There is a lot more to this, >> involving how progress is made in ML (open data, open source, open models, >> in general open science and associated communities, see e.g., OpenAi [3], >> Distill [4], and many others). In any event we need build community and >> gain new skills if we want to be able to develop and apply state of the art >> machine learning algorithms to network data, at scale. The bottom line is >> that it will be difficult if not impossible to be effective in the ML space >> if we ourselves don't understand how it works and further, if we can build >> explainable systems (noting that explaining what the individual neurons in >> a deep neural network are doing is notoriously difficult; that said much >> progress is being made). So we want to build explainable, end-to-end >> trained systems, and to accomplish this we ourselves need to understand how >> these algorithms work, but in training and in inference. >> >> This email is already TL;DR but I'll add one more here: We need to learn >> control, not just prediction. Since we live in an inherently adversarial >> environment we need to take advantage of Reinforcement Learning as well as >> the various attacks being formulated against ML; [5] gives one interesting >> example of attacks against policy networks using adversarial examples. See >> also slides 31 and 32 of [6] for some more on this topic. >> >> I hope some of this gets us thinking about the problems we need to solve >> in order to be successful in the ML space. There's plenty more of this on >> http://www.1-4-5.net/~dmm/ml and http://www.1-4-5.net/~dmm/vita.html. >> I'm looking forward to the discussion. >> >> Thanks, >> >> --dmm >> >> >> >> >> [0] http://packetpushers.net/podcast/podcasts/pq-show-107-a >> pplicability-machine-learning-networking/ >> >> [1] http://sebastianruder.com/transfer-learning/index.html >> [2] http://datascience.ibm.com/blog/the-mathematics-of-machine-learning/ >> [3] https://openai.com/blog/ >> [4] http://distill.pub/ >> [5] http://rll.berkeley.edu/adversarial/arXiv2017_AdversarialAttacks.pdf >> [6] http://www.1-4-5.net/~dmm/ml/talks/2016/cor_ml4networking.pptx >> >> >> _______________________________________________ >> IDNET mailing list >> IDNET@ietf.org >> https://www.ietf.org/mailman/listinfo/idnet >> >> > > > -- > Syed Rehman > > -- Adeel Rehman 978-551-5511
- [Idnet] A few ideas/suggestions to get us going David Meyer
- Re: [Idnet] A few ideas/suggestions to get us goi… Rana Pratap Sircar
- Re: [Idnet] A few ideas/suggestions to get us goi… Henk Birkholz
- Re: [Idnet] A few ideas/suggestions to get us goi… David Meyer
- Re: [Idnet] A few ideas/suggestions to get us goi… David Meyer
- Re: [Idnet] A few ideas/suggestions to get us goi… David Meyer
- Re: [Idnet] A few ideas/suggestions to get us goi… Adeel Rehman
- Re: [Idnet] A few ideas/suggestions to get us goi… Pedro Martinez-Julia
- Re: [Idnet] A few ideas/suggestions to get us goi… David Meyer
- Re: [Idnet] A few ideas/suggestions to get us goi… João Paulo S. Medeiros
- Re: [Idnet] A few ideas/suggestions to get us goi… Pedro Martinez-Julia
- Re: [Idnet] A few ideas/suggestions to get us goi… João Paulo S. Medeiros
- Re: [Idnet] A few ideas/suggestions to get us goi… David Meyer
- [Idnet] FPS game traffic datasets... Re: A few id… grenville armitage