A Secure Conjunctive Keywords Search over Encrypted Cloud Data Against Inclusion-Relation Attack

There exists a specific security issue in symmetric searchable encryption that, when doing CKS(Conjunctive Keywords Search), the trapdoors and search results may reveal the relationships between the keywords being searched. For example, if the search result of keywords set A is the superset of keywords set B´s, it indicates A is a subset of B by a high chance. Most existing search methods that support CKS suffer from such inclusion-relation (IR) attacks. We define measurements on IR security and propose CKS-SE, a secure CKS scheme based on bloom filter that achieves IR-secure by randomizing and integrating expressions of trapdoors. Experiments show that the average false positives are within an acceptable rate, and the performance of CKS-SE is among the best ones.