Typical ones in no particular order: fraud; obscuring crime, espionage, or covert activity; manipulating your competitors or markets; skirting regulations. Quite a lot of low-level organized crime.
A lot of it is transnational and many countries are complicit so there is relatively little you can do to stop it. If you use data at risk of this then systems have to be designed under the assumption that it is going to happen. It has spread and become worse over time.
It is a bit like FinCEN data in that if you work with it long enough you'll see a lot more going on in it than it is your job to notice.
alt Hacker News
Typical ones in no particular order: fraud; obscuring crime, espionage, or covert activity; manipulating your competitors or markets; skirting regulations. Quite a lot of low-level organized crime.
A lot of it is transnational and many countries are complicit so there is relatively little you can do to stop it. If you use data at risk of this then systems have to be designed under the assumption that it is going to happen. It has spread and become worse over time.
It is a bit like FinCEN data in that if you work with it long enough you'll see a lot more going on in it than it is your job to notice.