On the public citation graph
Scalable, High-Performance, and Generalized Subtree Data Anonymization Approach for Apache Spark
0 signed · 74 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.3083openalex-snapshot
SaC‐FRAPP: a scalable and cost‐effective framework for privacy preservation over big data on cloud
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/10.1007/978-3-319-59463-7_37openalex-snapshot
DPHKMS: An Efficient Hybrid Clustering Preserving Differential Privacy in Spark
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/10.1007/s10586-017-1167-yopenalex-snapshot
An experimental analysis of limitations of MapReduce for iterative algorithms on Spark
inferredcites →https://doi.org/10.1016/j.datak.2008.12.001openalex-snapshot
Privacy-preserving data publishing for cluster analysis
inferredcites →https://doi.org/10.1016/j.ins.2020.07.066openalex-snapshot
DI-Mondrian: Distributed improved Mondrian for satisfaction of the L-diversity privacy model using Apache Spark
inferredcites →https://doi.org/10.1016/j.jcss.2014.02.005openalex-snapshot
A survey of emerging threats in cybersecurity
inferredcites →https://doi.org/10.1016/j.jcss.2014.02.007openalex-snapshot
A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud
inferredcites →https://doi.org/10.1016/j.jksuci.2019.08.006openalex-snapshot
Improved l-diversity: Scalable anonymization approach for Privacy Preserving Big Data Publishing
inferredcites →https://doi.org/10.1016/j.knosys.2016.06.012openalex-snapshot
kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data
inferredcites →https://doi.org/10.1080/24751839.2020.1819633openalex-snapshot
Secure data outsourcing in presence of the inference problem: issues and directions
inferredcites →https://doi.org/10.1109/access.2016.2577036openalex-snapshot
Big Privacy: Challenges and Opportunities of Privacy Study in the Age of Big Data
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/ic2e.2014.43openalex-snapshot
A Scalable K-Anonymization Solution for Preserving Privacy in an Aging-in-Place Welfare Intercloud
inferredcites →https://doi.org/10.1109/icccnt45670.2019.8944778openalex-snapshot
A Scalable ($\alpha, k$)-Anonymization Approach using MapReduce for Privacy Preserving Big Data Publishing
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.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/icosec49089.2020.9215250openalex-snapshot
An Ensemble Learning Approach for Privacy–Quality–Efficiency Trade-Off in Data Analytics
inferredcites →https://doi.org/10.1109/infocom.2014.6848002openalex-snapshot
Achieving k-anonymity in privacy-aware location-based services
inferredcites →https://doi.org/10.1109/isi.2008.4565028openalex-snapshot
A framework for privacy-preserving cluster analysis
inferredcites →https://doi.org/10.1109/pst.2016.7906962openalex-snapshot
Towards privacy-preserving classification in neural networks
inferredcites →https://doi.org/10.1109/tc.2014.2360516openalex-snapshot
Proximity-Aware Local-Recoding Anonymization with MapReduce for Scalable Big Data Privacy Preservation in Cloud
inferredcites →https://doi.org/10.1109/tkde.2007.1015openalex-snapshot
Anonymizing Classification Data for Privacy Preservation
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/10.1145/1142473.1142499openalex-snapshot
Injecting utility into anonymized datasets
inferredcites →https://doi.org/10.1145/1749603.1749605openalex-snapshot
Privacy-preserving data publishing
inferredcites →https://doi.org/10.1145/3341698openalex-snapshot
Synthesizing differentially private programs
inferredcites →https://doi.org/10.1186/s40537-016-0059-yopenalex-snapshot
Big data privacy: a technological perspective and review
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/10.3390/electronics9101732openalex-snapshot
In-Memory Data Anonymization Using Scalable and High Performance RDD Design
inferredcites →https://doi.org/10.4018/ijdwm.2018040101openalex-snapshot
Privacy-Preserving Hybrid K-Means
inferredcites →https://doi.org/10.5120/19788-0531openalex-snapshot
Comparing Apache Spark and Map Reduce with Performance Analysis using K-Means
inferredcites →https://doi.org/10.5220/0003391100000551openalex-snapshot
HANDLING DATA SKEW IN MAPREDUCE
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/10.5555/2870614.2870620openalex-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.
inferred← citeshttps://doi.org/10.1007/978-3-031-94571-7_7openalex-snapshot
Building FAIR-Compliant Lakehouses with FLAMI
inferred← citeshttps://doi.org/10.1007/978-3-032-00624-0_2openalex-snapshot
Prink: $$k_s$$-Anonymization for Streaming Data in Apache Flink
inferred← citeshttps://doi.org/10.1007/s11227-021-03958-3openalex-snapshot
DHkmeans-ℓdiversity: distributed hierarchical K-means for satisfaction of the ℓ-diversity privacy model using Apache Spark
inferred← citeshttps://doi.org/10.1007/s13042-025-02910-8openalex-snapshot
Optimizing k-anonymity with automated generalization trees: a study on classification utility
inferred← citeshttps://doi.org/10.1016/j.jisa.2024.103756openalex-snapshot
A divide-and-conquer approach to privacy-preserving high-dimensional big data release
inferred← citeshttps://doi.org/10.1016/j.seta.2022.102152openalex-snapshot
Anonymization of distribution feeder data using statistical distribution and parameter estimation approach
inferred← citeshttps://doi.org/10.1109/confluence60223.2024.10463211openalex-snapshot
Amazon Product Recommendation System Using Apache Spark
inferred← citeshttps://doi.org/10.1109/fit67061.2025.11333617openalex-snapshot
A Context-Aware Adaptive Differential Privacy for Privacy-Aware Users in Mobile Crowd Sensing
inferred← citeshttps://doi.org/10.1109/iccd63220.2024.00028openalex-snapshot
Interpretable Risk-aware Access Control for Spark: Blocking Attack Purpose Behind Actions
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/icet66147.2025.11321444openalex-snapshot
Big Data Analytics for Polio Surveillance in Balochistan: Insights from Apache Spark
inferred← citeshttps://doi.org/10.1109/icosst69113.2025.11315386openalex-snapshot
Scalable Deep Learning Frameworks for Cyberbullying Detection in Social Media
inferred← citeshttps://doi.org/10.1109/icosst69113.2025.11315458openalex-snapshot
Big Data Analysis of Dark Matter Distribution in the Milky Way with Gaia DR3, Machine Learning, and Apache Spark
inferred← citeshttps://doi.org/10.1109/icosst69113.2025.11315490openalex-snapshot
Data Driven Approach for Early Risk Assessment of Cardiovascular Disease through Logistic Regression
inferred← citeshttps://doi.org/10.1109/iisec54230.2021.9672355openalex-snapshot
Kernel Virtual Machine based High Performance Environment for Grid and Jungle Computing
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/10.1145/3530809openalex-snapshot
A Survey on Cyber Situation-awareness Systems: Framework, Techniques, and Insights
inferred← citeshttps://doi.org/10.1145/3774755openalex-snapshot
The BigFAIR Architecture: Enabling Big Data Analytics in FAIR-compliant Repositories
inferred← citeshttps://doi.org/10.11591/ijece.v14i4.pp4686-4696openalex-snapshot
Big data anonymization using Spark for enhanced privacy protection
inferred← citeshttps://doi.org/10.1371/journal.pone.0285212openalex-snapshot
A distributed computing model for big data anonymization in the networks
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/app13106257openalex-snapshot
Optimization of the Join between Large Tables in the Spark Distributed Framework
inferred← citeshttps://doi.org/10.3390/electronics10101215openalex-snapshot
A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach
inferred← citeshttps://doi.org/10.3390/electronics11091449openalex-snapshot
Group Privacy: An Underrated but Worth Studying Research Problem in the Era of Artificial Intelligence and Big Data
inferred← citeshttps://doi.org/10.3390/math11020401openalex-snapshot
Efficient Associate Rules Mining Based on Topology for Items of Transactional Data
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.