@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00077983,
 author = {菊池, 浩明 and 佐久間, 淳 and Hiroaki, Kikuchi and Jun, Sakuma},
 book = {コンピュータセキュリティシンポジウム2011 論文集},
 issue = {3},
 month = {Oct},
 note = {プライバシー保護データマイニングには，安全なマーケティングや匿名のヘルスケア，安全な疫学など多くの潜在的応用がある．本稿では，集合を秘匿したままで複数の集合の交わりの大きさだけを比較するプロトコルを提案する．提案方式はBloomフィルタの内積の大きさを予測する．固定長のフィルタの為，通信効率が高い．, Privacy-Preserving Data mining has many potential applications including private marketing, anonymous healthcare, and secure epidemiology. This paper proposes a new scheme for comparison of cardinalities of intersection of given pair of private subsets without revealing any element of intersections. The proposed scheme estimates the size of intersection based on the scalar product of the corresponding Bloom filters with constant size of bits. The scheme is efficient in terms of communication.},
 pages = {516--521},
 publisher = {情報処理学会},
 title = {Bloomフィルタを用いたマッチング数の秘匿比較},
 volume = {2011},
 year = {2011}
}