I have a big data set of fake transactions for a company. Each row contains the username, credit card number, time, device used, and amount of money in the transaction. I need to classify each transaction as either malicious or not malicious and I am lost for ideas on where to start. Doing it by hand would be silly.
I was thinking possibly checking for how often a credit card is used, if it is consistently used at a certain time, or if it is used from lots of different devices (iOS AND Android, as an example) would be possible starting places. I'm still fairly new to all this and ML. Would there be some ML algorithm optimal for this problem?
Also, side question: what would be a good place to host the 600 or so GB of data for cheaps?