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Measuring and Protecting Privacy in the Always-On Era
Dan Feldman
,
Eldar Haber
Department of Computer Science
Faculty of Law
Research output
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peer-review
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Keyphrases
Adding Noise
20%
Always-on
100%
Computational Methods
20%
Computational Solutions
20%
Data Privacy
40%
Data Sensitivity
20%
Data Utility
60%
Differential Privacy
40%
Individual Privacy
60%
Information Gathering
20%
Information Use
20%
Internet of Things
20%
Internet of Things Devices
60%
Internet of Things Services
20%
Internet Use
20%
Legal Method
20%
Mining Practice
20%
New Computational Model
20%
Personal Assistant
20%
Policy Choice
20%
Privacy Protection
60%
Privacy Regulation
20%
Protecting Privacy
100%
Regulatory Approach
20%
Regulatory Framework
20%
Regulatory Mechanism
20%
Sectoral Approach
40%
Sectoral Regulation
20%
Sectorial
20%
Service Provider
40%
Smartphone
20%
Technological Change
20%
Technological Innovation
20%
Technological Progress
20%
Technological Solutions
20%
User Data
20%
Utility Protection
20%
World Wide Web
40%
Computer Science
Computational Method
33%
Computational Modeling
33%
Computational Solution
33%
Data Mining
33%
Differential Privacy
66%
Individual Privacy
100%
Information Gathering
33%
Internet of Things Device
100%
Internet-Of-Things
66%
Personal Assistant
33%
Privacy Protection
66%
Protect Privacy
66%
Protecting Privacy
100%
Risk Individual
33%
Service Provider
66%
Technological Change
33%
Technological Development
33%
Technological Solution
33%
User Data
33%
Engineering
Computational Solution
33%
Data User
33%
Individual Risk
33%
Internet of Things Device
100%
Internet-Of-Things
66%
Mobile Phones
33%
Sectoral
100%
Service Provider
66%
Technological Development
33%
Technological Innovation
33%
Technological Solution
33%
Economics, Econometrics and Finance
Industry
100%
Invention Process
100%
Regulatory Framework
100%
Technological Change
100%
Mathematics
Data Mining
33%
Internet of Things Device
100%
Internet-Of-Things
66%
Probability Theory
66%