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Flexible data anonymization using ARX—Current status and challenges ahead
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Datafly: a system for providing anonymity in medical data
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Statistical Confidentiality: Principles and Practice
inferredcites →https://doi.org/10.1007/978-3-319-23633-9_6openalex-snapshot
Putting Statistical Disclosure Control into Practice: The ARX Data Anonymization Tool
inferredcites →https://doi.org/10.1007/978-3-319-45381-1_11openalex-snapshot
Correcting Finite Sampling Issues in Entropy l-diversity
inferredcites →https://doi.org/10.1007/978-3-319-50272-4openalex-snapshot
Statistical Disclosure Control for Microdata: Methods and Applications in R
inferredcites →https://doi.org/10.1007/978-3-319-57358-8openalex-snapshot
Data Privacy: Foundations, New Developments and the Big Data Challenge
inferredcites →https://doi.org/10.1007/978-3-540-71703-4_18openalex-snapshot
Efficient k-Anonymization Using Clustering Techniques
inferredcites →https://doi.org/10.1007/978-3-540-75520-3_40openalex-snapshot
k-Anonymization with Minimal Loss of Information
inferredcites →https://doi.org/10.1007/s10115-015-0906-8openalex-snapshot
Managing dimensionality in data privacy anonymization
inferredcites →https://doi.org/10.1007/s10618-005-0007-5openalex-snapshot
Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation
inferredcites →https://doi.org/10.1007/s10618-007-0078-6openalex-snapshot
A recursive search algorithm for statistical disclosure assessment
inferredcites →https://doi.org/10.1016/j.ijmedinf.2019.03.006openalex-snapshot
Privacy-enhancing ETL-processes for biomedical data
inferredcites →https://doi.org/10.1017/cbo9781107337756openalex-snapshot
Secure Multiparty Computation and Secret Sharing
inferredcites →https://doi.org/10.1038/sdata.2017.171openalex-snapshot
Open University Learning Analytics dataset
inferredcites →https://doi.org/10.1093/jamia/ocv004openalex-snapshot
R-U policy frontiers for health data de-identification
inferredcites →https://doi.org/10.1109/cbms.2017.105openalex-snapshot
A Tool for Optimizing De-identified Health Data for Use in Statistical Classification
inferredcites →https://doi.org/10.1109/icde.2005.42openalex-snapshot
Data Privacy through Optimal k-Anonymization
inferredcites →https://doi.org/10.1109/icde.2006.1openalex-snapshot
L-diversity: privacy beyond k-anonymity
inferredcites →https://doi.org/10.1109/icde.2006.101openalex-snapshot
Mondrian Multidimensional K-Anonymity
inferredcites →https://doi.org/10.1109/icde.2007.367856openalex-snapshot
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
inferredcites →https://doi.org/10.1109/icde.2016.7498286openalex-snapshot
Collaborative analytics for data silos
inferredcites →https://doi.org/10.1109/icde.2017.175openalex-snapshot
Efficient Exploration of Telco Big Data with Compression and Decaying
inferredcites →https://doi.org/10.1109/icdmw.2009.15openalex-snapshot
Efficient Anonymizations with Enhanced Utility
inferredcites →https://doi.org/10.1109/infocom.2016.7524584openalex-snapshot
Graph-based privacy-preserving data publication
inferredcites →https://doi.org/10.1109/jbhi.2017.2676880openalex-snapshot
A Scalable and Pragmatic Method for the Safe Sharing of High-Quality Health Data
inferredcites →https://doi.org/10.1109/jsac.2017.2659078openalex-snapshot
Information Credibility Modeling in Cooperative Networks: Equilibrium and Mechanism Design
inferredcites →https://doi.org/10.1109/jstsp.2015.2425798openalex-snapshot
Privacy or Utility in Data Collection? A Contract Theoretic Approach
inferredcites →https://doi.org/10.1109/secpri.2003openalex-snapshot
2003 Symposium on Security and Privacy, 2003.
inferredcites →https://doi.org/10.1109/socialcom-passat.2012.52openalex-snapshot
Flash: Efficient, Stable and Optimal K-Anonymity
inferredcites →https://doi.org/10.1109/tkde.2005.99openalex-snapshot
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
inferredcites →https://doi.org/10.1109/tkde.2015.2435777openalex-snapshot
t-Closeness through Microaggregation: Strict Privacy with Enhanced Utility Preservation
inferredcites →https://doi.org/10.1111/1467-9574.00097openalex-snapshot
Statistical methods for some simple disclosure limitation rules
inferredcites →https://doi.org/10.1126/science.aad9295openalex-snapshot
Comment on “Unique in the shopping mall: On the reidentifiability of credit card metadata”
inferredcites →https://doi.org/10.1142/s0218488502001648openalex-snapshot
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
inferredcites →https://doi.org/10.1142/s021848850200165xopenalex-snapshot
ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION
inferredcites →https://doi.org/10.1145/1247480.1247554openalex-snapshot
Hiding the presence of individuals from shared databases
inferredcites →https://doi.org/10.1145/1386118.1386123openalex-snapshot
Workload-aware anonymization techniques for large-scale datasets
inferredcites →https://doi.org/10.1145/2347736.2347755openalex-snapshot
A few useful things to know about machine learning
inferredcites →https://doi.org/10.1145/2422604.2422611openalex-snapshot
Non-interactive differential privacy
inferredcites →https://doi.org/10.1145/775047.775089openalex-snapshot
Transforming data to satisfy privacy constraints
inferredcites →https://doi.org/10.1158/1055-9965.epi-17-0172openalex-snapshot
Protecting Privacy in Large Datasets—First We Assess the Risk; Then We Fuzzy the Data
inferredcites →https://doi.org/10.1186/1472-6947-12-66openalex-snapshot
Estimating the re-identification risk of clinical data sets
inferredcites →https://doi.org/10.1186/s12911-016-0287-2openalex-snapshot
Efficient and effective pruning strategies for health data de-identification
inferredcites →https://doi.org/10.1197/jamia.m1241openalex-snapshot
Effects of Data Anonymization by Cell Suppression on Descriptive Statistics and Predictive Modeling Performance
inferredcites →https://doi.org/10.1197/jamia.m2716openalex-snapshot
Protecting Privacy Using k-Anonymity
inferredcites →https://doi.org/10.1197/jamia.m3144openalex-snapshot
A Globally Optimal k-Anonymity Method for the De-Identification of Health Data
inferredcites →https://doi.org/10.1201/9781420091502openalex-snapshot
Introduction to Privacy-Preserving Data Publishing
inferredcites →https://doi.org/10.1371/journal.pone.0028071openalex-snapshot
A Systematic Review of Re-Identification Attacks on Health Data
inferredcites →https://doi.org/10.1371/journal.pone.0120592openalex-snapshot
A Game Theoretic Framework for Analyzing Re-Identification Risk
inferredcites →https://doi.org/10.14778/1453856.1453874openalex-snapshot
Privacy-preserving anonymization of set-valued data
inferredcites →https://doi.org/10.14778/2350229.2350255openalex-snapshot
Publishing microdata with a robust privacy guarantee
inferredcites →https://doi.org/10.14778/3231751.3231757openalex-snapshot
Data synthesis based on generative adversarial networks
inferredcites →https://doi.org/10.1515/popets-2018-0004openalex-snapshot
SafePub: A Truthful Data Anonymization Algorithm With Strong Privacy Guarantees
inferredcites →https://doi.org/10.2307/41703503openalex-snapshot
Business Intelligence and Analytics: From Big Data to Big Impact
inferredcites →https://doi.org/10.3414/me16-01-0012openalex-snapshot
The Importance of Context: Risk-based De-identification of Biomedical Data
inferredcites →https://doi.org/10.4018/ijsse.2015040104openalex-snapshot
Risk-Based Privacy-Aware Information Disclosure
inferredcites →https://doi.org/10.48550/arxiv.1808.01113openalex-snapshot
How to Avoid Reidentification with Proper Anonymization
inferredcites →https://doi.org/10.5555/1855711.1855731openalex-snapshot
Airavat: security and privacy for MapReduce
inferredcites →https://doi.org/10.5555/2612156.2612157openalex-snapshot
Achieving k-anonymity Using Improved Greedy Heuristics for Very Large Relational Databases
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A clustering‐based anonymization approach for privacy‐preserving in the healthcare cloud
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Visualizing the Risks of De-anonymization in High-Dimensional Data
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Iterative local search for preserving data privacy
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Differentially-private data synthetisation for efficient re-identification risk control
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Smart Anonymity: a mechanism for recommending data anonymization algorithms based on data profiles for IoT environments
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Bridging Legal Methodology and Ethical Considerations: A Novel Approach Applied to Challenges of Data Harvesting
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Phantom Anonymization: Adversarial testing for membership inference risks in anonymized health data
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Towards a data privacy-predictive performance trade-off
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TAE: Text anonymization evaluator
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sdcMicro: AI-assisted statistical disclosure control of microdata in R
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Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
inferred← citeshttps://doi.org/10.1038/s41597-022-01202-yopenalex-snapshot
Autonomic aging – A dataset to quantify changes of cardiovascular autonomic function during healthy aging
inferred← citeshttps://doi.org/10.1038/s41597-022-01561-6openalex-snapshot
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A case study comparing anonymized and synthetic health insurance claims data for medication safety assessments
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A Review of Anonymization for Healthcare Data
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Open tools for quantitative anonymization of tabular phenotype data: literature review
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Anonymize or synthesize? Privacy-preserving methods for heart failure score analytics
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Data Anonymization for Open Science: A Case Study
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Additional file 2 of EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation
Editorial review for independent work. ICSAC — the Institute for Complexity
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