第 1 回バイオメトリクス研究会 ( 早稲田大学 ) THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS Proceedings of Biometrics Workshop,169
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1 THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS Proceedings of Biometrics Workshop, , s hayashi@kom.comm.waseda.ac.jp, ohki@suou.waseda.jp Wolf attack based on speech synthesis using LP-residual signal Shohei HAYASHI, Tetsushi OHKI, Naohisa KOMATSU, and Jiro KATTO Faculty of Science and Engineering, Waseda University, Okubo, Shinjuku-ku, Tokyo , Japan Faculty of Science and Engineering, Waseda University, Okubo, Shinjuku-ku, Tokyo , Japan s hayashi@kom.comm.waseda.ac.jp, ohki@suou.waseda.jp Abstract In this paper, we suggest a method of creation of voice that allows the Wolf attack against speaker recognition system. The Wolf attacks using the vulnerability of specific algorithms may be difficult to create a natural biological information because of the matching algorithm dependency. Therefore, we propose the linear predictive coding and LP-residual signal which extracted from voice of swindler and a method of Wolf speech synthesis using the Wolf template and indicate the possibility of Wolf attack that does not depend on the matching algorithm. Key words speaker recognition system, Wolf attack, speech synthesis 1. IC FAR(False Acceptance Rate) FAR FAR WAP(Wolf Attack Probability) [1] [4] ( ) 80
2 2. i ) WAP [2] [3] WAP ii ) FAR(False Acceptance Rate) FAR WAP [1] S s T t s t match(s, t) {accept, reject} WAP W AP = max s S Ave P r[match(s, t) = accept] (1) t T P r[match(s, t) = accept] s t Ave X t X max X t T s S s X WAP [4]
3 !"# ) *!&#!"# $ %!&# $' %!&# '!"# $ %!&# '!"# 2!"# (!"# a ) LBG+splitting [5] LPC(Linear Predictive Coding) LPC b ) 3 F C LPC N 1. f (0 < f < = F ) N LPC a f (n) y(f) = N a f (n)y(f n) (2) 2. LPC r(f) r(f) = y(f) N a f (n)y(f n) (3) 3. w c(n) (0 < c < = C) LPC a f (n) LPC a f (n) C z = argmin c d{a f (n), w c (n) C c=1} (4) a f (n) = w z(n) (5) LPC a f (n) w c (n) d{a f (n), w c (n)} D f,c = d{a f (n), w c (n)} 1 N {a f (n) w c (n)} N 2 (6) 4. LPC a f (n) r(f) 82
4 y (f) = N a f (n)y(f n) + r(f) (7) F VQ [6] [7] LBG+splitting 4 LPC LSP LPC LPC LPC F C N f F, c C, n N t c (n) a f (n) LPC 256 d f d f = 1 N 16 {t c (n) a f (n)} 2 (8) LPC (1) WAP WAP W w WAP W AP = Ave Ave w W t T P r[match(w, t) = accept] (9) ATR [8] c ) LPC LPC LBG+splitting 256 d ) ATR 1 10msec LPC WAP
5 第1回バイオメトリクス研究会 早稲田大学 の話者照合システムに対するウルフ攻撃実験を行った なお 4. 2 登録者テンプレートのクラス使用頻度 使用する特徴量が異なる認証システムに対する本提案手法の有 4. 1 節での攻撃実験では 極端に高い攻撃性能が得られた 効性を確認するために テンプレートとして利用する特徴量と 特にテンプレートに LPC を用いたシステムでは登録者本人が して 16 次元 LPC と 10 次元 LSP の 2 種類を利用して実験を 照合を行い照合が成功する確率よりもウルフ音声を用いて攻撃 行った この実験結果を図 5,6 に示す が成功する確率の方が高いという結果が得られた また この 図 5 の攻撃実験では使用するウルフテンプレートによる WAP の違いが見られなかった 以上のことから全登録者のテンプ レートに全ての人に共通な生体情報を含むクラスがそれぞれ含 まれ 作成したウルフ音声に含まれる生体特徴がそのクラスに 近いものばかりとなり 攻撃確率が上昇したのではないかと考 えた そこで 登録者の個人テンプレート 256 クラスの使用頻 度を調査することで特定のクラスが偏って使用されていないか を確認しようと考えた 3. 3 節において述べたように式 (8) で 求める距離が最小となるクラスとの距離を照合用のスコア値と して用いている このとき距離が最小となるクラスを使用クラ スとし ある一人の女性 A さんの登録テンプレートについて ウルフテンプレートを使用しない通常の話者照合時 ウルフ音 声を用いたウルフ攻撃時のそれぞれにおける各クラスの使用頻 図 5 登録テンプレートの特徴量として LPC を用いたシステムに対し てウルフ攻撃を行った際の WAP 度とその距離を調査した また ウルフテンプレートの種類に 関係なく高い WAP を示した図 5 の登録者テンプレートとして LPC を用いたシステムを調査対象とした この調査結果を図 7,8,9,10 に示す 図 6 登録テンプレートの特徴量として LSP を用いたシステムに対し 図 7 通常の照合における女性 A のテンプレートのクラス使用頻度 てウルフ攻撃を行った際の WAP 図 5,6 における FAR と FRR は使用した話者照合システム を通常の話者照合実験にて評価したものである FAR は他人 受入れ率 FRR は本人拒否率を表し FAR と FRR の交点 のエラー率を等価エラー率 (EER:Equal Error Rate) とする cwap,fwap,mwap はぞれぞれ共通 (Common) テンプレー ト 女性 (female) テンプレート 男性 (male) テンプレートを ウルフテンプレートとして使用した際の WAP を示している 登録テンプレートの特徴量として LPC を用いたシステムに対 しては EER=約 10%のときに使用テンプレートに係わらずど の WAP も約 98%を示し LSP を用いたシステムに対しては EER=約 3%のとき cwap,mwap=約 95% fwap=約 90%を 図 8 通常の照合における女性 A のテンプレートのクラス使用時の 距離 示した 本提案方式により作成したウルフ音声が LPC,LSP い ずれの特徴量を用いたテンプレートに対しても高いウルフ攻撃 確率を示すことが確認された 84
6 9 A 10 A % 5 40% A WAP EER= 10% WAP= 98% LSP EER= 3% WAP= 95% WAP HMM [1] M.Une,A.Otsuka,H.Imai, Wolf Attack Probability: a New Security Measure in Biometrisc-Based Authentication Systems, SCIS2007,Jan 2007 [2] Y.Tanabe,K.Yoshizoe,H.Imai, A Study on security evaluation Metodology in FingerVein Authentication Systems, SCIS2008,pp.3B4-2,Jan 2008 [3] [4] SCIS2012,Jan 2012 [5] Y.Linde, A.Buzo, R.M.Gray, An Algorithm for Vector Quantizer Design, IEEE Trans.Commun., Vol.COM-28, No.1, pp.88-95,1980 [6] A Vol.J75-A, No.4, pp , [7] CELP 32 5 pp [8] APPBLA, sdb.html 5. LPC 85
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