These are good info. In my past life, I oversaw the web monetization pipeline as part of my job. Click fault detection was part of it. It is a hard problem a

These are good info. In my past life, I oversaw the web monetization pipeline as part of my job. Click fault detection was part of it. It is a hard problem and there's no 100% foolproof solution. As in your case, it's nearly impossible to detect click fault real time as the clicks streaming in. We batch-processed the clicks throughout the day and do daily billing settlement at the end of the day. It's easier to detect click fault over a period of time. Obvious bots are filtered out, like the search engine crawlers. For click fault, it's impossible to distinguish one-off click as a user click or fault click. We tried to catch repeated offenders. we looked for duplicate clicks (same ip, same agent, other client attributes) against certain targets (same product, product categories, merchants, etc) over a period of times (1-minute, 5-minute, 30-minute, hours, etc). We also built historic click stats on the targets so we can check the average click pattern against historic stats (yesterday, week ago, month ago, year ago). We ran quick checks every 1 minute and 5 minutes to detect unusual click patterns. These were mainly for detecting DOS attack against our site or against certain products. We actually had a realtime reaction mechanism to deal with it: slow down the requests, throw up CAPTCHA, redirect to a generic page, or block ip at routers. Every couple hours, we batch processed the clicks so far and ran the exhausting checks to flag suspicious clicks. At the end of the day, definite fault clicks were thrown out, moderate suspicious clicks were grouped and reviewed by human. It's a fine balance to flag less suspicious clicks since there's money involved. The sophisticate click fault I've seen involved a distributed botnet clicking from hundreds of IP all over the world doing slow clicks during the day. We found out because it's targeting a product category of a merchant and causing unusual click stats compared to historic pattern.