PUBCRAWL: Protecting Users and Businesses from CRAWLers

Web crawlers are automated tools that browse the web to retrieve and analyze information. Although crawlers are useful tools that help users to find content on the web, they may also be malicious. Unfortunately, unauthorized (malicious) crawlers are increasingly becoming a threat for service providers because they typically collect information that attackers can abuse for spamming, phishing, or targeted attacks. In particular, social networking sites are frequent targets of malicious crawling, and there were recent cases of scraped data sold on the black market and used for blackmailing. In this paper, we introduce PUBCRAWL, a novel approach for the detection and containment of crawlers. Our detection is based on the observation that crawler traffic significantly differs from user traffic, even when many users are hidden behind a single proxy. Moreover, we present the first technique for crawler campaign attribution that discovers synchronized traffic coming from multiple hosts. Finally, we introduce a containment strategy that leverages our detection results to efficiently block crawlers while minimizing the impact on legitimate users. Our experimental results in a large, well-known social networking site (receiving tens of millions of requests per day) demonstrate that PUBCRAWL can distinguish between crawlers and users with high accuracy. We have completed our technology transfer, and the social networking site is currently running PUB-CRAWL in production.