  The web bots have been blamed for consuming large amount of Internet traffic
and undermining the interest of the scraped sites for years. Traditional bot
detection studies focus mainly on signature-based solution, but advanced bots
usually forge their identities to bypass such detection. With increasing cloud
migration, cloud providers provide new opportunities for an effective bot
detection based on big data to solve this issue. In this paper, we present a
behavior-based bot detection scheme called BotGraph that combines sitemap and
convolutional neural network (CNN) to detect inner behavior of bots.
Experimental results show that BotGraph achieves ~95% recall and precision on
35-day production data traces from different customers including the Bing
search engine and several sites.
