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In-Memory Data Anonymization Using Scalable and High Performance RDD Design
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-33495-6_7openalex-snapshot
A Distributed Method Based on Mondrian Algorithm for Big Data Anonymization
inferredcites →https://doi.org/10.1007/978-3-030-36938-5_40openalex-snapshot
SparkDA: RDD-Based High-Performance Data Anonymization Technique for Spark Platform
inferredcites →https://doi.org/10.1007/978-3-319-90775-8_29openalex-snapshot
Anonymizing k-NN Classification on MapReduce
inferredcites →https://doi.org/10.1007/978-981-10-5421-1_8openalex-snapshot
A Privacy Preserving Platform for MapReduce
inferredcites →https://doi.org/10.1109/bigdata.2017.8258492openalex-snapshot
A top-down k-anonymization implementation for apache spark
inferredcites →https://doi.org/10.1109/bigdatacongress.2017.15openalex-snapshot
Scalable, Efficient Anonymization with INCOGNITO - Framework & Algorithm
inferredcites →https://doi.org/10.1109/icde.2005.143openalex-snapshot
Top-Down Specialization for Information and Privacy Preservation
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.2018.00171openalex-snapshot
PRIMA: An End-to-End Framework for Privacy at Scale
inferredcites →https://doi.org/10.1109/services.2014.41openalex-snapshot
Challenges for MapReduce in Big Data
inferredcites →https://doi.org/10.1109/tkde.2008.52openalex-snapshot
Anonymization by Local Recoding in Data with Attribute Hierarchical Taxonomies
inferredcites →https://doi.org/10.1109/tpds.2013.48openalex-snapshot
A Scalable Two-Phase Top-Down Specialization Approach for Data Anonymization Using MapReduce on Cloud
inferredcites →https://doi.org/10.1109/trustcom.2013.235openalex-snapshot
Combining Top-Down and Bottom-Up: Scalable Sub-tree Anonymization over Big Data Using MapReduce on Cloud
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/10.1145/1142473.1142499openalex-snapshot
Injecting utility into anonymized datasets
inferredcites →https://doi.org/10.1145/1456441.1456453openalex-snapshot
A survey of state-of-the-art in anonymity metrics
inferredcites →https://doi.org/10.1186/s40537-017-0104-5openalex-snapshot
Improving MapReduce privacy by implementing multi-dimensional sensitivity-based anonymization
inferredcites →https://doi.org/10.1186/s40537-018-0149-0openalex-snapshot
Experimenting sensitivity-based anonymization framework in apache spark
inferredcites →https://doi.org/10.5220/0007685200610071openalex-snapshot
Anonylitics: From a Small Data to a Big Data Anonymization System for Analytical Projects
inferredcites →https://doi.org/10.5555/1556439.1556440openalex-snapshot
Enhanced P-Sensitive K-Anonymity Models for Privacy Preserving Data Publishing
inferredcites →https://doi.org/10.5555/2870614.2870620openalex-snapshot
A Systematic Comparison and Evaluation of k-Anonymization Algorithms for Practitioners
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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inferred← citeshttps://doi.org/10.1109/iccbdai66607.2025.11388590openalex-snapshot
Optimizing Breast Cancer Classification Accuracy with Hybrid Deep Learning and Advanced Image Processing
inferred← citeshttps://doi.org/10.1109/iccsc71566.2026.11650399openalex-snapshot
UPAS: A Unified Privacy-Preserving Anonymization Framework for Spark Platform
inferred← citeshttps://doi.org/10.1109/icomet57998.2023.10099175openalex-snapshot
Generative Adversarial Networks for Anomaly Detection: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1109/icosst69113.2025.11315386openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iisec54230.2021.9672355openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iisec56263.2022.9998305openalex-snapshot
Cyber Security's Silver Bullet - A Systematic Literature Review of AI-Powered Security
inferred← citeshttps://doi.org/10.1145/3484945openalex-snapshot
A Novel Hybrid Approach for Multi-Dimensional Data Anonymization for Apache Spark
inferred← citeshttps://doi.org/10.11591/ijece.v14i4.pp4686-4696openalex-snapshot
Big data anonymization using Spark for enhanced privacy protection
inferred← citeshttps://doi.org/10.1186/s42400-024-00345-2openalex-snapshot
Unitanony: a fine-grained and practical anonymization framework for better data utility
inferred← citeshttps://doi.org/10.32604/cmc.2023.036438openalex-snapshot
Zero Watermarking Algorithm for Medical Image Based on Resnet50-DCT
inferred← citeshttps://doi.org/10.3390/electronics10050589openalex-snapshot
Scalable, High-Performance, and Generalized Subtree Data Anonymization Approach for Apache Spark
inferred← citeshttps://doi.org/10.3390/electronics10101215openalex-snapshot
A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach
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Efficient Associate Rules Mining Based on Topology for Items of Transactional Data
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