Mobile ad fraud is an industry wide problem Adjust is intent on taking on. Find out more about mobile click fraud, and how we tackle it, here.

You may have seen our latest announcement over on our product feed: an upgrade to our systems that filters click injections even more effectively. Here, we explain the story behind it.

China’s mobile internet population is close to hitting 800 million, but this comes with growing rates of fraud. Why is fraud so widespread in China, and what can be done to stop it?

CAAF has helped bring education, the key to defending against fraud, to the masses, and allowed us to share what we’ve learned together as one group.

The biggest unspoken truth of 2018 is this: the market often views fraud as a good thing.

Spoofed attributions are as old as attribution itself. As soon as it was clear that there was a chance to randomly steal credit for users installing an app organically...

We’ve talked about the theory behind ad fraud: that is, how we think about the problem.

For many, machine learning is just a catch-all buzzword. After all, you could say it’s just a bunch of ‘if statements’, and (in some cases) you wouldn’t be too far off.

Moving beyond the types of fraud we discussed in part 1 of our theory series, it’s time we looked at the lack of distinction between fraud solutions.

In this article, we break down ad fraud in a new way - dividing the mass of methods between two very distinct approaches.