VLDB09勉強会 Session27 Privacy2

Session 27 : Privacy II 担当：川本淳平（京都大学） Session 27 : Privacy II 担当：川本（京大）【 VLDB2009 勉強会】

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） Alice の購入商品と一致 T 1 : {Beer, Diapers} T 2 : { Wine , Diapers , Brush } T 3 : {Beer, Wine, Brush} トランザクション DB

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）どっちが Alice か分からない T 1 : {Beer, Diapers} T 2 : { Wine , Diapers , Brush } T 3 : {Beer, Wine, Brush} T 4 : {Beer, Wine , Diapers , Brush } トランザクション DB

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）やっぱり T 2 = Alice と特定可能 T 1 : {Beer, Diapers} T 2 : {Wine, Diapers, Brush} T 3 : {Beer, Wine, Brush} T 4 : { Beer , Wine, Diapers, Brush} トランザクション DB

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）

[object Object],Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) Session 27 : Privacy II 担当：川本（京大）例：下記トランザクションを 2 -anonymity を満たすよう変換 T 1 : { a 1 } T 2 : { a 1 , a 2 } T 3 : { b 1 ,b 2 } T 4 : { b 1 , b 2 } T 5 : { a 1 , a 2 , b 2 } T 6 : { a 1 , a 2 , b 2 } T 7 : { a 1 , a 2 , b 1 , b 2 } ALL A B a 1 a 2 b 1 b 2 一般化階層構造

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） P A P B P AB -> { A } -> { A } -> { B } -> { B } -> { A, B } -> { A, B } -> { A, B } T 1 : { a 1 } T 2 : { a 1 , a 2 } T 3 : { b 1 ,b 2 } T 4 : { b 1 , b 2 } T 5 : { a 1 , a 2 , b 2 } T 6 : { a 1 , a 2 , b 2 } T 7 : { a 1 , a 2 , b 1 , b 2 } ALL A B a 1 a 2 b 1 b 2 一般化階層構造

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） P B P AB -> { a 1 } -> { B } -> { B } -> { A, B } -> { A, B } -> { A, B } P a1a2 -> { a 1 , a 2 } P a1 ALL A B a 1 a 2 b 1 b 2 一般化階層構造 T 1 : { a 1 } T 2 : { a 1 , a 2 } T 3 : { b 1 ,b 2 } T 4 : { b 1 , b 2 } T 5 : { a 1 , a 2 , b 2 } T 6 : { a 1 , a 2 , b 2 } T 7 : { a 1 , a 2 , b 1 , b 2 }

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） P A P b1b2 P a1a2B -> { A } -> { A } -> { b 1 ,b 2 } -> { b 1 ,b 2 } -> { a 1 , a 2 , B } -> { a 1 , a 2 , B } -> { a 1 , a 2 , B } ALL A B a 1 a 2 b 1 b 2 一般化階層構造 T 1 : { a 1 } T 2 : { a 1 , a 2 } T 3 : { b 1 ,b 2 } T 4 : { b 1 , b 2 } T 5 : { a 1 , a 2 , b 2 } T 6 : { a 1 , a 2 , b 2 } T 7 : { a 1 , a 2 , b 1 , b 2 }

Anonymization of Set-Valued Data via Top-Down, Local Generalization ( He and Naughton ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）グラフは著者らのスライドより引用

K-Automorphism: A General Framework For Privacy Preserving Network Publication ( Zou , Chen , and Özsu ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）唯一 4 本の枝を持つすなわち Bob Bob の友達は 4 人

K-Automorphism: A General Framework For Privacy Preserving Network Publication ( Zou , Chen , and Özsu ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） 2 -Automorphism の例

K-Automorphism: A General Framework For Privacy Preserving Network Publication ( Zou , Chen , and Özsu ) ,[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大） k=2 の例手順 1 手順 2 手順 3 本来のグラフ P 12 P 22 P 12 P 22 P 12 P 22

K-Automorphism: A General Framework For Privacy Preserving Network Publication ( Zou , Chen , and Özsu ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）階層構造を用いて最適な一般化を行う ,[object Object],[object Object],[object Object],ID Zipcode Gender Salary 1 91110 F 30K 2 91210 M 50K 3 91210 M 60K 4 91330 F 30K 5 52210 F 40K 6 52220 F 40K 7 52240 F 60K 8 52210 M 50K

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）階層構造を用いて最適な一般化を行う ,[object Object],[object Object],[object Object],ID Zipcode Gender Salary 1 9 1110 F 30K 2 9 1210 M 50K 3 9 1210 M 60K 4 9 1330 F 30K 5 5 2210 F 40K 6 5 2220 F 40K 7 5 2240 F 60K 8 5 2210 M 50K

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）階層構造を用いて最適な一般化を行う 30K 40K 50K 60K 30K -40K 50K -60K 30K-60K Salary の階層構造 ID Zipcode Gender Salary 1 9 1110 F 30K 2 9 1210 M 50K 3 9 1210 M 60K 4 9 1330 F 30K 5 5 2210 F 40K 6 5 2220 F 40K 7 5 2240 F 60K 8 5 2210 M 50K ID Zipcode Gender Salary 1 91110 F 30K-40K 2 91210 M 50K 3 91210 M 60K 4 91330 F 30K-40K 5 52210 F 30K-40K 6 52220 F 30K-40K 7 52240 F 60K 8 52210 M 50K

[object Object],[object Object],[object Object],[object Object],Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) Session 27 : Privacy II 担当：川本（京大）階層構造を用いて最適な一般化を行う ID Zipcode Gender Salary 1 91110 F 30K-40K 2 91210 M 50K 3 91210 M 60K 4 91330 F 30K-40K 5 52210 F 30K-40K 6 52220 F 30K-40K 7 52240 F 60K 8 52210 M 50K ID Zipcode Gender Salary 1 91110 F 50K 2 91210 M 30K-40K 3 91210 M 30K-40K 4 91330 F 60K 5 52210 F 60K 6 52220 F 50K 7 52240 F 30K-40K 8 52210 M 30K-40K 30K 40K 50K 60K 30K -40K 50K -60K 30K-60K Salary の階層構造

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）通常偽タプルの追加 ID Zipcode Salary 1 91210 40K 2 91220 30K 3 91220 50K ID Zipcode Salary 1 91210 30K-40K 2 91220 30K-60K 3 91220 50K-60K ID Zipcode Salary 1 91210 40K 2 91220 30K 3 91220 50K 60K

Distribution-based Microdata Anonymization ( Koudas , Srivastava , Yu , Zhang ) ,[object Object],[object Object],[object Object],Session 27 : Privacy II 担当：川本（京大）グラフは著者らのスライドより引用

VLDB09勉強会 Session27 Privacy2

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VLDB09勉強会 Session27 Privacy2