As pervasive computing environments become popular, RFID tags are introduced into our daily life. However, there exists a privacy problem that an adversary can trace users' behavior by linking the tag's ID. Although a hash-chain scheme can solve this privacy problem, the scheme needs a long identification time or a large amount of memory. In this paper, we propose an efficient identification scheme using Bloom filters, which are space-efficient probabilistic data structures. Our Bloom pre-calculation scheme provides a high-speed identification with a small amount of memory by storing pre-calculated outputs of the tags in Bloom filters.