Author(s): Cecilia S. Gal, Paul B. Kantor, Michael E. Lesk
Edition: 1
Publisher: Springer
Year: 2009
Language: English
Pages: 139
front-matter......Page 1
Introduction......Page 9
Theoretical Attacks on the Problem......Page 11
Practical Approaches to the Problem......Page 12
Plus Ça Change…......Page 13
Why Does Privacy Matter?......Page 14
References......Page 17
The Environment Has Changed......Page 19
Intelligence and Crime-Fighting......Page 20
Three Truths about Intelligence......Page 21
Origins of Intelligence Policy......Page 22
Responsibility for Domestic (Counter) Intelligence......Page 23
A Possible Solution......Page 25
Introduction......Page 28
Rethinking Computing$^{1}$......Page 31
History......Page 34
Future......Page 35
Concluding Remarks......Page 39
References......Page 41
Intelligence in the Age of Global Commerce and Terror......Page 42
The Evolution of Conceptualizations of Privacy and Regulatory Orientations......Page 43
Information Privacy and Intelligence......Page 46
Abuses, Regulation, and Oversight of Information-Sharing and Intelligence......Page 47
Public and Private Information-Sharing......Page 49
Building Effective Intelligence Oversight......Page 50
References......Page 51
Privacy and Security......Page 53
Sensitivity and Authority......Page 56
Second Set......Page 58
Privacy Technology Areas......Page 60
References......Page 64
Introduction......Page 65
A Verbal Paradox......Page 66
Constellations of Concepts......Page 67
Questions Characterizing Privacy Protection$^{2}$......Page 68
References......Page 69
kACTUS 2: Privacy Preserving in Classification Tasks Using k-Anonymity......Page 71
Introduction and Motivation......Page 72
Related Work......Page 73
Problem Formulation......Page 74
How a Complying Node Is Selected for Compensation by Swapping......Page 76
The kACTUS-2 Algorithm......Page 77
Experimental Evaluation......Page 79
Datasets......Page 80
Comparing to Other k-Anonymity Algorithms......Page 81
Information Loss......Page 87
References......Page 88
Introduction......Page 90
Background and Problem Formulation......Page 91
Logistic Regression......Page 93
Secure Logistic Regression......Page 94
Logistic Regression over Horizontally Partitioned Data......Page 95
Logistic Regression over Vertically Partitioned Data......Page 96
Discussion and Future Directions......Page 98
Conclusion......Page 100
References......Page 101
Introduction......Page 103
The Los Angeles Landscape......Page 105
Implementation......Page 106
Reporting......Page 108
Local and National Implications......Page 109
References......Page 110
Introduction......Page 112
LiveJournal Blog Data......Page 113
Global, Individual, and Relational Statistics......Page 115
Community and Evolution Statistics......Page 118
Conclusion......Page 121
References......Page 122
Introduction......Page 123
Technical Approach......Page 124
Better Accountability by Linking Unstructured and Structured Data......Page 125
Improved Accuracy Management through Better Entity Disambiguation......Page 126
Privacy-Governed Operation......Page 127
References......Page 128
Introduction......Page 130
Dataset Analysis and Modeling......Page 133
Graphical Exploration and Transformations......Page 134
Verification of Linear Regression Assumptions......Page 135
Interaction Variables......Page 137
Cross Validation......Page 138
Regularized Regression......Page 139
Choice of Final Model......Page 140
Conclusions......Page 142
References......Page 143
A Municipalities......Page 144
back-matter......Page 146
