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1.

電子ブック
ＥＢ
1. Data and Applications Security XXIII
Ehud Gudes, Takeo Kanade, Jaideep Vaidya
出版情報: Springer eBooks Computer Science , Springer Berlin Heidelberg, 2009
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2.

電子ブック
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2. Privacy Preserving Data Mining
Jaideep Vaidya, Christopher Wade Clifton, Michael Zhu, Yu Michael Zhu
出版情報: Springer eBooks Computer Science , Springer US, 2006
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目次情報: 続きを見る
Privacy and Data Mining / 1：
What is Privacy? / 2：
Individual Identifiability / 2.1：
Measuring the Intrusiveness of Disclosure / 2.2：
Solution Approaches / Problems / 3：
Data Partitioning Models / 3.1：
Perturbation / 3.2：
Secure Multi-party Computation / 3.3：
Secure Circuit Evaluation / 3.3.1：
Secure Sum / 3.3.2：
Predictive Modeling for Classification / 4：
Decision Tree Classification / 4.1：
A Perturbation-Based Solution for ID3 / 4.2：
A Cryptographic Solution for ID3 / 4.3：
ID3 on Vertically Partitioned Data / 4.4：
Bayesian Methods / 4.5：
Horizontally Partitioned Data / 4.5.1：
Vertically Partitioned Data / 4.5.2：
Learning Bayesian Network Structure / 4.5.3：
Summary / 4.6：
Predictive Modeling for Regression / 5：
Introduction and Case Study / 5.1：
Case Study / 5.1.1：
What are the Problems? / 5.1.2：
Weak Secure Model / 5.1.3：
Secure Estimation of Regression Coefficients / 5.2：
Diagnostics and Model Determination / 5.2.2：
Security Analysis / 5.2.3：
An Alternative: Secure Powell's Algorithm / 5.2.4：
Summary and Future Research / 5.3：
Finding Patterns and Rules (Association Rules) / 6：
Randomization-based Approaches / 6.1：
Randomization Operator / 6.1.1：
Support Estimation and Algorithm / 6.1.2：
Limiting Privacy Breach / 6.1.3：
Other work / 6.1.4：
Cryptography-based Approaches / 6.2：
Inference from Results / 6.2.1：
Descriptive Modeling (Clustering, Outlier Detection) / 7：
Clustering / 7.1：
Data Perturbation for Clustering / 7.1.1：
EM-clustering for Horizontally Partitioned Data / 7.2：
K-means Clustering for Vertically Partitioned Data / 7.2.2：
Outlier Detection / 7.3：
Distance-based Outliers / 7.3.1：
Basic Approach / 7.3.2：
Modified Secure Comparison Protocol / 7.3.3：
Computation and Communication Analysis / 7.3.6：
Future Research - Problems remaining / 7.3.8：
References
Index
Privacy and Data Mining / 1：
What is Privacy? / 2：
Individual Identifiability / 2.1：
3.

図書
図書
3. プライバシー保護データマイニング
J.ヴァイダヤ, C.W.クリフトン, Y.M.ズー著 ; 嶋田茂, 清水將吾訳
出版情報: 東京 : シュプリンガー・ジャパン, 2010.11  ix, 156p ; 21cm
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4.

電子ブック
ＥＢ
4. Data and Applications Security XXIII
Ehud Gudes, Takeo Kanade, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer Berlin Heidelberg, 2009
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5.

電子ブック
ＥＢ
5. Computer Security - ESORICS 2014
Kutylowski, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer International Publishing, 2014
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6.

電子ブック
ＥＢ
6. Computer Security - ESORICS 2014
Kutylowski, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer International Publishing, 2014
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7.

電子ブック
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7. Information Systems Security
Shyamasundar, Virendra Singh, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer International Publishing, 2017
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8.

電子ブック
ＥＢ
8. Privacy Preserving Data Mining
Jaideep Vaidya, Christopher Wade Clifton, Michael Zhu, Yu Michael Zhu, Christopher W. Clifton
出版情報: SpringerLink Books - AutoHoldings , Springer US, 2006
所蔵情報: loading…
目次情報: 続きを見る
Privacy and Data Mining / 1：
What is Privacy? / 2：
Individual Identifiability / 2.1：
Measuring the Intrusiveness of Disclosure / 2.2：
Solution Approaches / Problems / 3：
Data Partitioning Models / 3.1：
Perturbation / 3.2：
Secure Multi-party Computation / 3.3：
Secure Circuit Evaluation / 3.3.1：
Secure Sum / 3.3.2：
Predictive Modeling for Classification / 4：
Decision Tree Classification / 4.1：
A Perturbation-Based Solution for ID3 / 4.2：
A Cryptographic Solution for ID3 / 4.3：
ID3 on Vertically Partitioned Data / 4.4：
Bayesian Methods / 4.5：
Horizontally Partitioned Data / 4.5.1：
Vertically Partitioned Data / 4.5.2：
Learning Bayesian Network Structure / 4.5.3：
Summary / 4.6：
Predictive Modeling for Regression / 5：
Introduction and Case Study / 5.1：
Case Study / 5.1.1：
What are the Problems? / 5.1.2：
Weak Secure Model / 5.1.3：
Secure Estimation of Regression Coefficients / 5.2：
Diagnostics and Model Determination / 5.2.2：
Security Analysis / 5.2.3：
An Alternative: Secure Powell's Algorithm / 5.2.4：
Summary and Future Research / 5.3：
Finding Patterns and Rules (Association Rules) / 6：
Randomization-based Approaches / 6.1：
Randomization Operator / 6.1.1：
Support Estimation and Algorithm / 6.1.2：
Limiting Privacy Breach / 6.1.3：
Other work / 6.1.4：
Cryptography-based Approaches / 6.2：
Inference from Results / 6.2.1：
Descriptive Modeling (Clustering, Outlier Detection) / 7：
Clustering / 7.1：
Data Perturbation for Clustering / 7.1.1：
EM-clustering for Horizontally Partitioned Data / 7.2：
K-means Clustering for Vertically Partitioned Data / 7.2.2：
Outlier Detection / 7.3：
Distance-based Outliers / 7.3.1：
Basic Approach / 7.3.2：
Modified Secure Comparison Protocol / 7.3.3：
Computation and Communication Analysis / 7.3.6：
Future Research - Problems remaining / 7.3.8：
References
Index
Privacy and Data Mining / 1：
What is Privacy? / 2：
Individual Identifiability / 2.1：
9.

電子ブック
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9. Algorithms and Architectures for Parallel Processing: 22nd International Conference, ICA3PP 2022, Copenhagen, Denmark, October 10–12, 2022, Proceedings
Weizhi Meng, Rongxing Lu, Geyong Min, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer Nature, 2023
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10.

電子ブック
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10. Data and Applications Security and Privacy XXXIV: 34th Annual IFIP WG 11.3 Conference, DBSec 2020, Regensburg, Germany, June 25–26, 2020, Proceedings
Singhal, Jaideep Vaidya
出版情報: SpringerLink Books - AutoHoldings , Springer International Publishing, 2020
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