Search engines make the information retrieval task easier for the users. Highly ranking position in the search engine query results brings great benefits for websites. Some website owners interpret the link architecture to improve ranks. To handle the search engine spam problems, especially link farm spam, clique identification in the network structure would help a lot. This paper proposes a novel strategy to detect the spam based on K-Clique Percolation method. Data collected from website and classified with NaiveBayes Classification algorithm. The suspicious spam sites are analyzed for clique-attacks. Observations and findings were given regarding the spam. Performance of the system seems to be good in terms of accuracy.