Protecting Privacy through Homomorphic Encryption

Protecting Privacy through Homomorphic Encryption

Dai, Wei; Laine, Kim; Lauter, Kristin

Springer Nature Switzerland AG

01/2022

176

Dura

Inglês

9783030772864

15 a 20 dias

465

Descrição não disponível.
Part 1: Introduction to Homomorphic Encryption (Dai).- Part 2: Homomorphic Encryption Security Standard: Homomorphic Encryption Security Standard (Laine).- Part 3: Applications of Homomorphic Encryption: Privacy-preserving Data Sharing and Computation Across Multiple Data Providers with Homomorphic Encryption (Troncoso-Pastoriza).- Secure and Confidential Rule Matching for Network Traffic Analysis (Jetchev).- Trusted Monitoring Service (TMS) (Scott).- Private Set Intersection and Compute (Kannepalli).- Part IV Applications of Homomorphic Encryption (at the Private AI Bootcamp): Private Outsourced Translation for Medical Data (Viand).- HappyKidz: Privacy Preserving Phone Usage Tracking (Hastings).- i-SEAL2: Identifying Spam EmAiL with SEAL (Froelicher).- PRIORIS: Enabling Secure Suicidal Ideation Detection from Speech using Homomorphic Machine Learning (Natarajan).- Gimme That Model!: A Trusted ML Model Trading Protocol (Lee).- HEalth: Privately Computing on Shared Healthcare Data (Hales).- Private Movie Recommendations for Children (Wagh S).- Privacy-Preserving Prescription Drug Management Using Homomorphic Encryption (Youmans).
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whitepapers;privacy protection;cryptography;technology developments;computer science applications;optimization