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Does anyone know of a quick way I can come up to speed on how to use machine learning? I am trying to use Raindom forest to classify if a device is an IoT device or not based on a couple network features. Thanks

 

ƆԀ S₱▓Ɇ▓cs: i7 6ʇɥפᴉƎ00K (4.4ghz), Asus DeLuxe X99A II, GT҉X҉1҉0҉8҉0 Zotac Amp ExTrꍟꎭe),Si6F4Gb D???????r PlatinUm, EVGA G2 Sǝʌǝᘉ5ᙣᙍᖇᓎᙎᗅᖶt, Phanteks Enthoo Primo, 3TB WD Black, 500gb 850 Evo, H100iGeeTeeX, Windows 10, K70 R̸̢̡̭͍͕̱̭̟̩̀̀̃́̃͒̈́̈́͑̑́̆͘͜ͅG̶̦̬͊́B̸͈̝̖͗̈́, G502, HyperX Cloud 2s, Asus MX34. פN∩SW∀S 960 EVO

Just keeping this here as a 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11 minutes ago, BuckGup said:

Does anyone know of a quick way I can come up to speed on how to use machine learning? I am trying to use Raindom forest to classify if a device is an IoT device or not based on a couple network features. Thanks

 

As said before, do you really need to use ML for that?

 

If so, do you have enough data for it?

 

If so, just throw it at sciki, tune some parameters and see if the results are ok.

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28 minutes ago, Electronics Wizardy said:

If your goal is to just tell if something is a IOT device, there are probably much simplier methods, by looking at things like the OUI, hostname, and user agent.

 

18 minutes ago, igormp said:

As said before, do you really need to use ML for that?

 

If so, do you have enough data for it?

 

If so, just throw it at sciki, tune some parameters and see if the results are ok.

Yes I need to use machine learning. It should be able to identify the device as IoT with no user interaction needed. I'm using a dataset from online. 

 

So from my understanding, tell me if I'm wrong, I would take a machine learning tool like sciki or tensorflow and use random forest on a dataset and tell it to look at specific features. Then what? Does it just keep looking at these features and self checking or where does human intervention come in so I can get a precision and accuracy numbers? Thanks

ƆԀ S₱▓Ɇ▓cs: i7 6ʇɥפᴉƎ00K (4.4ghz), Asus DeLuxe X99A II, GT҉X҉1҉0҉8҉0 Zotac Amp ExTrꍟꎭe),Si6F4Gb D???????r PlatinUm, EVGA G2 Sǝʌǝᘉ5ᙣᙍᖇᓎᙎᗅᖶt, Phanteks Enthoo Primo, 3TB WD Black, 500gb 850 Evo, H100iGeeTeeX, Windows 10, K70 R̸̢̡̭͍͕̱̭̟̩̀̀̃́̃͒̈́̈́͑̑́̆͘͜ͅG̶̦̬͊́B̸͈̝̖͗̈́, G502, HyperX Cloud 2s, Asus MX34. פN∩SW∀S 960 EVO

Just keeping this here as a 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7 minutes ago, BuckGup said:

So from my understanding, tell me if I'm wrong, I would take a machine learning tool like sciki or tensorflow and use random forest on a dataset and tell it to look at specific features.

Steer away from tensorflow since you're just a beginner and focus on scikitlearn.

 

7 minutes ago, BuckGup said:

Then what? Does it just keep looking at these features and self checking or where does human intervention come in so I can get a precision and accuracy numbers? Thanks

Yes. What you'll need to do is prepare the data for your model, pick the right parameters (by trial and error), let it run with your data and check your metrics (F1-score is a nice final metric that takes into account many other metrics). Repeat this process until you have a reasonable result.

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12 minutes ago, BuckGup said:

I would take a machine learning tool like sciki or tensorflow and use random forest on a dataset and tell it to look at specific features.

What features would you be looking for that identify the device as IoT? You can't tell just by looking at it... and if you know the feature list you can definitely figure out a simpler way to identify it.

13 minutes ago, BuckGup said:

Then what? Does it just keep looking at these features and self checking or where does human intervention come in so I can get a precision and accuracy numbers? Thanks

Typically machine learning requires a labelled dataset; you show it a bunch of things which have been manually identified by a human and the machine tries to learn to do the same, correcting itself when it makes a mistake (as defined by your manual labels). I must stress that this dataset would need to contain a minimum of a few thousand manually identified and preferably quite varied samples; a couple dozen aren't going to cut it.

 

I'm not sure where you got the random forests from, it's just one of many possible models and not necessarily the best one for what you want to do.

Don't ask to ask, just ask... please 🤨

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1 minute ago, Sauron said:

What features would you be looking for that identify the device as IoT? You can't tell just by looking at it... and if you know the feature list you can definitely figure out a simpler way to identify it.

From what they said so far, it sounds like a college assignment.

 

2 minutes ago, Sauron said:

I must stress that this dataset would need to contain a minimum of a few thousand manually identified and preferably quite varied samples; a couple dozen aren't going to cut it.

 

I'm not sure where you got the random forests from, it's just one of many possible models and not necessarily the best one for what you want to do.

If we assume it's a school assignment, then it's safe to also assume that the professor did give a reasonable open dataset for that, and made they try random forest in this specific case.

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Just now, igormp said:

From what they said so far, it sounds like a college assignment.

 

If we assume it's a school assignment, then it's safe to also assume that the professor did give a reasonable open dataset for that, and made they try random forest in this specific case.

In a college assignment the professor would (or at least should) have at least introduced the students to a ML toolkit before giving them this task 🤔

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1 minute ago, Sauron said:

In a college assignment the professor would (or at least should) have at least introduced the students to a ML toolkit before giving them this task 🤔

Maybe they did and the student just didn't pay attention, or it's just a bad teacher, or teaching a framework wasn't within the scope and let the students pick whatever they wanted in whichever language (happened to me and that was ok), who knows.

This isn't the first topic asking for help with a ML assignment that I've seen in this sub.

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4 hours ago, Sauron said:

In a college assignment the professor would (or at least should) have at least introduced the students to a ML toolkit before giving them this task 🤔

 

4 hours ago, igormp said:

Maybe they did and the student just didn't pay attention, or it's just a bad teacher, or teaching a framework wasn't within the scope and let the students pick whatever they wanted in whichever language (happened to me and that was ok), who knows.

This isn't the first topic asking for help with a ML assignment that I've seen in this sub.

Hahah no I'm actually doing research and have to use it. My college has a very shitty computer science department and they teach nothing about it.

ƆԀ S₱▓Ɇ▓cs: i7 6ʇɥפᴉƎ00K (4.4ghz), Asus DeLuxe X99A II, GT҉X҉1҉0҉8҉0 Zotac Amp ExTrꍟꎭe),Si6F4Gb D???????r PlatinUm, EVGA G2 Sǝʌǝᘉ5ᙣᙍᖇᓎᙎᗅᖶt, Phanteks Enthoo Primo, 3TB WD Black, 500gb 850 Evo, H100iGeeTeeX, Windows 10, K70 R̸̢̡̭͍͕̱̭̟̩̀̀̃́̃͒̈́̈́͑̑́̆͘͜ͅG̶̦̬͊́B̸͈̝̖͗̈́, G502, HyperX Cloud 2s, Asus MX34. פN∩SW∀S 960 EVO

Just keeping this here as a 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1 minute ago, BuckGup said:

 

Hahah no I'm actually doing research and have to use it. My college has a very shitty computer science department and they teach nothing about it.

Then have a quick look at this, then this.

FX6300 @ 4.2GHz | Gigabyte GA-78LMT-USB3 R2 | Hyper 212x | 3x 8GB + 1x 4GB @ 1600MHz | Gigabyte 2060 Super | Corsair CX650M | LG 43UK6520PSA
ASUS X550LN | i5 4210u | 12GB
Lenovo N23 Yoga

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