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Privacy-preserving Data Mining in Industry:

, In: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining,

Kenthapadi, Krishnaram ; Mironov, Ilya ; Thakurta, Abhradeep Guha - p. 840-841 , 2019

Link: https://dl.acm.org/doi/10.1145/3289600.3291384

RT 
T1 <cTitle>Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining</cTitle>: T1 <Title>Privacy-preserving Data Mining in Industry</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3291384&Exemplar=1&LAN=DE
				
A1 Kenthapadi, Krishnaram
A1 Mironov, Ilya
A1 Thakurta, Abhradeep Guha
PB ACM
YR 2019
K1 apple's differential privacy deployment for ios and macos
K1 differential privacy
K1 google's rappor
K1 linkedin salary
K1 local differential privacy
K1 microsoft's differential privacy deployment for collecting windows telemetry
K1 privacy breaches
K1 privacy case studies in industry
K1 privacy-preserving data mining
K1 privacy-preserving web analytics and reporting
K1 Security and privacy
K1 Security services
K1 Privacy-preserving protocols
K1 Database and storage security
K1 Data anonymization and sanitization
K1 Theory of computation
K1 Theory and algorithms for application domains
K1 Database theory
K1 Theory of database privacy and security
K1 Human and societal aspects of security and privacy
K1 Privacy protections
K1 Software and application security
K1 Domain-specific security and privacy architectures
SP 840
OP 841
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3289600.3291384
DO https://dl.acm.org/doi/10.1145/3289600.3291384
SF ELIB - SuUB Bremen

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