Papers by Kumar Chellapilla

Improving Cloaking Detection Using Search Query Popularity and Monetizability

Here’s another paper about detecting search engine spam, contemporary with Detecting Semantic Cloaking on the Web and, in fact, presented as a refinement to that paper. They don’t make any changes to the is this page spamming the search engine algorithm itself; rather, they optimize the scan for pages that are spamming the search engine, by looking at the spammers’ economic incentives.

It obviously does no good to make your site a prominent search hit for keywords that nobody ever searches for. Less obviously, since search engine spammers are trying to make money by sucking people into linkfarms full of ads, they should be focusing on keywords that lots of advertisers are interested in (monetizability in the paper’s jargon). Therefore, the search engine operator should focus its spam-detection efforts on the most-searched and most-advertised keywords. Once you identify a linkfarm, you can weed it out of all your keyword indexes, so this improves search results in the long tail as well as the popular case.

They performed a quick verification of this hypothesis with the help of logs of the 5000 most popular and 5000 most advertised search keywords, from the MSN search engine (now Bing). Indeed, the spam was strongly skewed toward both high ends—somewhat more toward monetizability than popularity.

That’s really all there is to say about this paper. They had a good hypothesis, they tested it, and the hypothesis was confirmed. I’ll add that this is an additional reason (besides just making money) for search engines to run their own ad brokerages, and a great example of the value of applying economic reasoning to security research.