<p>This seems to fall broadly into the regime of a <a href="https://en.wikipedia.org/wiki/Statistical_classification" rel="nofollow">classification problem</a> as you want to classify an outgoing communication as "contains proprietary information" or "does not contain proprietary information".  As such, any classification approach could be applied.  Neural Networks certainly seem like a valid approach, but you might also get good mileage out of Random Forests, Support Vector Machines, a Naive Bayes classifier, etc.</p>

<p>GA's are more aimed towards optimization than classification, so I wouldn't say that a GA, in and of itself, would map cleanly to solving this kind of problem. If GA's had applicability here, I think it would be more likely to be in terms of training a model rooted in one of the other techniques.     </p>

CC BY-SA 3.0
2016-08-14T05:57:55.947Z
2016-08-14T05:57:55.947Z
mindcrime
<p>I'm investigating applications of AI algorithms which can be used for data leakage detection and prevention within an intranet network (like <a href="https://en.wikipedia.org/wiki/Forcepoint" rel="nofollow">Forcepoint</a>). More specifically detecting traffic patterns. I'm new to this.</p>

<p>Which learning algorithms are most suitable for this goal? <a href="https://en.wikipedia.org/wiki/Evolutionary_algorithm" rel="nofollow">EA</a>, <a href="https://en.wikipedia.org/wiki/Genetic_algorithm" rel="nofollow">GA</a>, <a href="https://en.wikipedia.org/wiki/Artificial_neural_network" rel="nofollow">ANN</a> (which one) or something else?</p>

<learning-algorithms>
Which learning algorithms are suitable for data leakage detection and prevention?
kenorb
# Which learning algorithms are suitable for data leakage detection and prevention?

(Asked by: username_0 on 2016-08-13)

I'm investigating applications of AI algorithms which can be used for data leakage detection and prevention within an intranet network (like [Forcepoint](https://en.wikipedia.org/wiki/Forcepoint)). More specifically detecting traffic patterns. I'm new to this.

Which learning algorithms are most suitable for this goal? [EA](https://en.wikipedia.org/wiki/Evolutionary_algorithm), [GA](https://en.wikipedia.org/wiki/Genetic_algorithm), [ANN](https://en.wikipedia.org/wiki/Artificial_neural_network) (which one) or something else?

**Tags:** learning-algorithms


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## 1 answers

### Answer by username_1 on 2016-08-14. Score: 3 | Accepted answer

This seems to fall broadly into the regime of a [classification problem](https://en.wikipedia.org/wiki/Statistical_classification) as you want to classify an outgoing communication as "contains proprietary information" or "does not contain proprietary information". As such, any classification approach could be applied. Neural Networks certainly seem like a valid approach, but you might also get good mileage out of Random Forests, Support Vector Machines, a Naive Bayes classifier, etc.

GA's are more aimed towards optimization than classification, so I wouldn't say that a GA, in and of itself, would map cleanly to solving this kind of problem. If GA's had applicability here, I think it would be more likely to be in terms of training a model rooted in one of the other techniques.


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