How to detect frauds in advertising business using machine learning? I am very beginner to this world. I still learning the basics of Machine learning and AI but i have a problem at hand and i am not sure which technique or Algorithm can be applied on it.

I am working on Click-Fraud detection in advertising. I need to predict fraud and learn new frauds with ML.

The dataset I have is the view and click logs from adserver(Service Provider). This data have some fields few of them are listed below:

"auction_log_bid_id": null, 
"banner": 9407521, 
"browser": 0, 
"campaign": 2981976, 
"city": 94965, 
"clickword": null, 
"content_unit": 4335438, 
"country": 1, 
"external_profiledata": {}, 
"external_user_id": null, 
"flash_version": null, 
"id": 6665230893362053181, 
"ip_address": "80.187.103.98", 
"is_ssl": true, 
"keyword": "string"
"mobile_device": -1, 
"mobile_device_class": -1, 
"network": 268, 
"new_user_id": 6665230893362118717, 
"operating_system": 14, 
"profile_data": {}, 
"referrer": null, 
"screen_resolution": null, 
"server_id": 61, 
"state": 7, 
"target_url": "string"
"timestamp": 1551870000, 
"type": "CLICK_COMMAND", 
"user_agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 12_1_4 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/16D57", 
"user_id": null, 
"view_log_id": null


There are other fields.

I need to analyse these logs to find patterns for possible frauds but i am not sure where to start and which technique to use. e.g. Supervised, Unsupervised Semi-Supervised or Reinforcement Learning.
There are a couple of different ways you can go about this depending on what kind of data you have.

If you have labels or can separate the normal data from the fraudulent, you can perform either binary classification, or likely more usefully, anomaly detection.

In Anomaly Detection(which is typically now done via autoencoder) you train your model on the normal data, so it learns a compressed representation of that 'signal', from there it will be able to detect any sample that does not fit the learned representation(in theory).

Here is a link to a tutorial in keras: link