Analysing and evaluating syntactic privacy games via a recommender systems case study

Analysing and evaluating syntactic privacy games via a recommender systems case study

The probabilistic notion of differential privacy has emerged as a popular measure for systems that support interactive data release. Consequently, there exists a portfolio of mechanisms to achieve differential privacy. A complementary approach is to represent syntactic privacy notions such as anonym...

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Bibliografiske detaljer
Main Authors:	Ankele, R, Simpson, A
Format:	Conference item
Sprog:	English
Udgivet:	IEEE 2020

Lignende værker

Abstracting syntactic privacy notions via privacy games
af: Ankele, R, et al.
Udgivet: (2020)

Addressing syntactic privacy for privacy-preserving data analysis and data release
af: Ankele, R
Udgivet: (2020)

Applying the trustworthy remote entity to privacy-preserving multiparty computation: requirements and criteria for large-scale applications
af: Ankele, R, et al.
Udgivet: (2016)

Controlling privacy in recommender systems
af: Xin, Yu, et al.
Udgivet: (2015)

A Taxonomy of Syntactic Privacy Notions for Continuous Data Publishing
af: Adrian Tobar Nicolau, et al.
Udgivet: (2024-01-01)

Challenges in recommender systems : scalability, privacy, and structured recommendations
af: Xin, Yu, Ph. D. Massachusetts Institute of Technology
Udgivet: (2015)

On the performance of a trustworthy remote entity in comparison to secure multi-party computation
af: Ankele, R, et al.
Udgivet: (2017)

Whither the privacy breach case studies?
af: Simpson, A
Udgivet: (2016)

The Syntactic-Semantic Analyses of Sasak Demonstratives in Lombok
af: Sutarman Sutarman, et al.
Udgivet: (2020-09-01)

Review of Privacy-Preserving Research in Recommendation Systems
af: FENG Han, YI Huawei, LI Xiaohui, LI Rui
Udgivet: (2023-08-01)

Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems
af: Derek Lilienthal, et al.
Udgivet: (2024-01-01)

Privacy-preserving recommendation system based on social relationships
af: Simin Yu, et al.
Udgivet: (2024-02-01)

Privacy enhanced matrix factorization for recommendation with local differential privacy
af: Shin, Hyejin, et al.
Udgivet: (2018)

Existential abstractions for distributed reactive systems via syntactic transformations
af: D'Silva, V, et al.
Udgivet: (2007)

Privacy risk adaptive access control model via evolutionary game
af: Hongfa DING, et al.
Udgivet: (2019-12-01)

Privacy risk adaptive access control model via evolutionary game
af: Hongfa DING, et al.
Udgivet: (2019-12-01)

Syntactic analyses of discourse particles through the microvariation of Basque ote
af: Sergio Monforte
Udgivet: (2020-12-01)

Acoustic emission analyses of the hygrothermal ageing of glass syntactic foams
af: Grosjean François, et al.
Udgivet: (2011-12-01)

Building Analyses from Syntactic Inference in Local Languages: An HPSG Grammar Inference System
af: Kristen Howell, et al.
Udgivet: (2022-07-01)

Preserving data privacy in social recommendation
af: Shu-shu LIU, et al.
Udgivet: (2015-12-01)

Preserving data privacy in social recommendation
af: Shu-shu LIU, et al.
Udgivet: (2015-12-01)

Generating User Privacy-Controllable Synthetic Data for Recommendation Systems
af: Zhenxiang He, et al.
Udgivet: (2025-01-01)

Differential privacy in collaborative filtering recommender systems: a review
af: Peter Müllner, et al.
Udgivet: (2023-10-01)

Blockchain-Enabled Technique for Privacy- Preserved Medical Recommender System
af: Eric Appiah Mantey, et al.
Udgivet: (2023-01-01)

Optimal Forgery and Suppression of Ratings for Privacy Enhancement in Recommendation Systems
af: Javier Parra-Arnau, et al.
Udgivet: (2014-03-01)

Syntactic case and DP (in)visibility
af: Gabriela Alboiu
Udgivet: (2019-01-01)

A Secure and Privacy Preserved Parking Recommender System Using Elliptic Curve Cryptography and Local Differential Privacy
af: Awais Abdul Khaliq, et al.
Udgivet: (2022-01-01)

Personalized privacy protection method for group recommendation
af: Haiyan WANG, et al.
Udgivet: (2019-09-01)

Personalized privacy protection method for group recommendation
af: Haiyan WANG, et al.
Udgivet: (2019-09-01)

Toward Privacy-Preserving Personalized Recommendation Services
af: Cong Wang, et al.
Udgivet: (2018-02-01)

Survey on Privacy Protection Solutions for Recommended Applications
af: DONG Xiao-mei, WANG Rui, ZOU Xin-kai
Udgivet: (2021-09-01)

Personalized Privacy Protection-Preserving Collaborative Filtering Algorithm for Recommendation Systems
af: Bin Cheng, et al.
Udgivet: (2023-04-01)

A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems
af: Muhammad Asad, et al.
Udgivet: (2023-05-01)

A group preference-based privacy-preserving POI recommender system
af: Xiwei Wang, et al.
Udgivet: (2020-09-01)

Privacy-Aware Detection of Shilling Profiles on Arbitrarily Distributed Recommender Systems
af: Burcu Yilmazel, et al.
Udgivet: (2019-01-01)

A Survey on the use of Federated Learning in Privacy-Preserving Recommender Systems
af: Christos Chronis, et al.
Udgivet: (2024-01-01)

An efficient privacy-preserving point-of-interest recommendation model based on local differential privacy
af: Chonghuan Xu, et al.
Udgivet: (2022-12-01)

Russian case morphology and the syntactic categories /
af: Pesetsky, David Michael, author
Udgivet: (2013)

A “borderline case” of syntactic variation
af: Ellen Brandner
Udgivet: (2020-03-01)

Effectiveness of Sentence Scramble Games to Improve Syntactic Abilities for a Student with Hearing Impairment
af: Riza Asri Yeta, et al.
Udgivet: (2019-01-01)