Pay-Per-Click (PPC) ad networks charge advertisers for every click on their ads. Click-fraud happens when a user or an automated software clicks on an ad with a malicious intent and advertisers need to pay for those valueless clicks. Click-fraud has been proved to be a serious problem for the online advertisement industry. Although it has attracted much attention from the security community, the direct victims of click-fraud, the advertisers, still lack confidence in the click-fraud detection techniques. Among many forms of click-fraud, botnets with the automated clickers are the most severe ones. In this project, we present a technique for detecting automated clickers from the user side.