I'm investigating applications of AI algorithms which can be used for data leakage detection and prevention within an intranet network (like Forcepoint). More specifically detecting traffic patterns. I'm new to this.
This seems to fall broadly into the regime of a classification problem 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.