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A Solution for Privacy Protection in MapReduce

https://doi.org/10.1109/compsac.2012.70
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1097-024x(199706)27:6<701::aid-spe104>3.0.co;2-0openalex-snapshot
Value Numbering
inferredcites →https://doi.org/10.1007/11761679_29openalex-snapshot
Our Data, Ourselves: Privacy Via Distributed Noise Generation
inferredcites →https://doi.org/10.1007/11787006_1openalex-snapshot
Differential Privacy
inferredcites →https://doi.org/10.1007/11965893_2openalex-snapshot
Ask a Better Question, Get a Better Answer A New Approach to Private Data Analysis
inferredcites →https://doi.org/10.1007/3-540-48298-9_41openalex-snapshot
Data Swapping: Balancing Privacy against Precision in Mining for Logic Rules
inferredcites →https://doi.org/10.1007/978-3-540-30116-5_27openalex-snapshot
Privately Computing a Distributed k-nn Classifier
inferredcites →https://doi.org/10.1007/978-3-540-78478-4_1openalex-snapshot
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
inferredcites →https://doi.org/10.1007/978-3-540-79228-4_1openalex-snapshot
Differential Privacy: A Survey of Results
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.2007.367859openalex-snapshot
On Randomization, Public Information and the Curse of Dimensionality
inferredcites →https://doi.org/10.1109/icdm.2005.122openalex-snapshot
Privacy-Preserving Frequent Pattern Mining across Private Databases
inferredcites →https://doi.org/10.1109/icst.2008.63openalex-snapshot
An Evaluation of Two Bug Pattern Tools for Java
inferredcites →https://doi.org/10.1109/sfcs.1982.88openalex-snapshot
Protocols for secure computations
inferredcites →https://doi.org/10.1109/sp.2008.33openalex-snapshot
Robust De-anonymization of Large Sparse Datasets
inferredcites →https://doi.org/10.1137/1.9781611972757.9openalex-snapshot
Privacy-Preserving Classification of Customer Data without Loss of Accuracy
inferredcites →https://doi.org/10.1142/s0218488502001648openalex-snapshot
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
inferredcites →https://doi.org/10.1145/1055558.1055591openalex-snapshot
On the complexity of optimal K-anonymity
inferredcites →https://doi.org/10.1145/1065167.1065183openalex-snapshot
Simulatable auditing
inferredcites →https://doi.org/10.1145/1065167.1065184openalex-snapshot
Practical privacy
inferredcites →https://doi.org/10.1145/1217299.1217302openalex-snapshot
L -diversity
inferredcites →https://doi.org/10.1145/1394504.1394506openalex-snapshot
Securing Java code
inferredcites →https://doi.org/10.1145/1557019.1557090openalex-snapshot
Differentially private recommender systems
inferredcites →https://doi.org/10.1145/202530.202541openalex-snapshot
Java intermediate bytecodes
inferredcites →https://doi.org/10.1145/207110.207154openalex-snapshot
Global code motion/global value numbering
inferredcites →https://doi.org/10.1145/262009.262010openalex-snapshot
Programming languages for mobile code
inferredcites →https://doi.org/10.1145/306363.306382openalex-snapshot
Bytecode-based Java program analysis
inferredcites →https://doi.org/10.1145/335191.335438openalex-snapshot
Privacy-preserving data mining
inferredcites →https://doi.org/10.1145/772862.772865openalex-snapshot
Cryptographic techniques for privacy-preserving data mining
inferredcites →https://doi.org/10.1145/772862.772869openalex-snapshot
Randomization in privacy preserving data mining
inferredcites →https://doi.org/10.1145/773153.773173openalex-snapshot
Revealing information while preserving privacy
inferredcites →https://doi.org/10.1145/775047.775142openalex-snapshot
Privacy preserving association rule mining in vertically partitioned data
inferredcites →https://doi.org/10.1145/956750.956776openalex-snapshot
Privacy-preserving k -means clustering over vertically partitioned data
inferredcites →https://doi.org/10.5555/1182635.1164142openalex-snapshot
Towards robustness in query auditing
inferredcites →https://doi.org/10.5555/1855711.1855731openalex-snapshot
Airavat: security and privacy for MapReduce

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-319-63962-8_243-1openalex-snapshot
Scalable Big Data Privacy with MapReduce
inferred← citeshttps://doi.org/10.1007/978-3-319-77525-8_243openalex-snapshot
Scalable Big Data Privacy with MapReduce
inferred← citeshttps://doi.org/10.1007/978-981-10-5421-1_8openalex-snapshot
A Privacy Preserving Platform for MapReduce
inferred← citeshttps://doi.org/10.1016/j.procs.2016.02.037openalex-snapshot
Critical Study of Performance Parameters on Distributed File Systems Using MapReduce
inferred← citeshttps://doi.org/10.1016/j.procs.2022.11.340openalex-snapshot
A Novel Distributed Differential Privacy Preserving Based on Random Forest in Data Centers
inferred← citeshttps://doi.org/10.1088/1757-899x/782/2/022011openalex-snapshot
A Survey on Privacy-Preserving Data Mining Methods
inferred← citeshttps://doi.org/10.1109/iwbis.2016.7872886openalex-snapshot
A review of big data analytics in the biomedical field
inferred← citeshttps://doi.org/10.1109/lcn.2016.029openalex-snapshot
Sensitivity-Based Anonymization of Big Data
inferred← citeshttps://doi.org/10.1109/tbdata.2016.2608848openalex-snapshot
Big Data Privacy in Biomedical Research
inferred← citeshttps://doi.org/10.1109/trustcom/bigdatase/icess.2017.325openalex-snapshot
Implementing A Framework for Big Data Anonymity and Analytics Access Control
inferred← citeshttps://doi.org/10.22214/ijraset.2018.6055openalex-snapshot
Survey on Customized Privacy Preservation Model for Cloud Environment
inferred← citeshttps://doi.org/10.4018/978-1-4666-9840-6.ch102openalex-snapshot
Electronic records management - an old solution to a new problem: governments providing usable information to stakeholders
inferred← citeshttps://doi.org/10.4018/ijegr.2014100105openalex-snapshot
Electronic Records Management - An Old Solution to a New Problem
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amm.519-520.3openalex-snapshot
A Framework for Processing Water Resources Big Data and Application
inferred← citeshttps://doi.org/10.4108/eai.13-7-2018.163991openalex-snapshot
Protecting and Securing Sensitive Data in a Big Data Using Encryption
inferred← citeshttps://doi.org/10.5120/ijca2016910844openalex-snapshot
The Prototype for Implementation of Security Issue in Big Data Application using Hadoop Server
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