On the public citation graph
Privacy-Preserving Computation of Bayesian Networks on Vertically Partitioned Data
0 signed · 108 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known work and none has been retracted — and get a dated CiteStamped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/10.1006/inco.1998.2753openalex-snapshot
Distributed Cooperative Bayesian Learning Strategies
inferredcites →https://doi.org/10.1007/11496618_9openalex-snapshot
On Private Scalar Product Computation for Privacy-Preserving Data Mining
inferredcites →https://doi.org/10.1007/3-540-44634-6_16openalex-snapshot
Secure Multi-party Computational Geometry
inferredcites →https://doi.org/10.1007/3-540-46502-2_12openalex-snapshot
Collective, Hierarchical Clustering from Distributed, Heterogeneous Data
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/10.1007/3-540-48910-x_16openalex-snapshot
Public-Key Cryptosystems Based on Composite Degree Residuosity Classes
inferredcites →https://doi.org/10.1007/978-1-4612-2404-4_12openalex-snapshot
Learning Bayesian Networks is NP-Complete
inferredcites →https://doi.org/10.1007/978-3-540-24676-3_1openalex-snapshot
Efficient Private Matching and Set Intersection
inferredcites →https://doi.org/10.1007/978-3-540-30073-1_5openalex-snapshot
Experimental Analysis of Privacy-Preserving Statistics Computation
inferredcites →https://doi.org/10.1007/bf00994110openalex-snapshot
A Bayesian Method for the Induction of Probabilistic Networks from Data
inferredcites →https://doi.org/10.1007/bf02637154openalex-snapshot
Collective Mining of Bayesian Networks from Distributed Heterogeneous Data
inferredcites →https://doi.org/10.1007/s00145-001-0019-2openalex-snapshot
Privacy Preserving Data Mining
inferredcites →https://doi.org/10.1007/s001459910006openalex-snapshot
Security and Composition of Multiparty Cryptographic Protocols
inferredcites →https://doi.org/10.1016/b978-155860869-6/50066-4openalex-snapshot
Maintaining Data Privacy in Association Rule Mining
inferredcites →https://doi.org/10.1109/64.395352openalex-snapshot
Some privacy issues in knowledge discovery: the OECD personal privacy guidelines
inferredcites →https://doi.org/10.1109/icde.2005.230openalex-snapshot
Improved Privacy-Preserving Bayesian Network Parameter Learning on Vertically Partitioned Data
inferredcites →https://doi.org/10.1109/icdm.2003.1250908openalex-snapshot
On the privacy preserving properties of random data perturbation techniques
inferredcites →https://doi.org/10.1109/icdm.2004.10076openalex-snapshot
Privacy-Sensitive Bayesian Network Parameter Learning
inferredcites →https://doi.org/10.1109/secpri.2002.1004361openalex-snapshot
Collaborative filtering with privacy
inferredcites →https://doi.org/10.1109/sfcs.1986.25openalex-snapshot
How to generate and exchange secrets
inferredcites →https://doi.org/10.1109/tkde.2006.14openalex-snapshot
Random projection-based multiplicative data perturbation for privacy preserving distributed data mining
inferredcites →https://doi.org/10.1109/tkde.2008.167openalex-snapshot
Privacy-Preserving Kth Element Score over Vertically Partitioned Data
inferredcites →https://doi.org/10.1137/1.9781611972733.31openalex-snapshot
Learning Bayesian Network Structure from Distributed Data
inferredcites →https://doi.org/10.1137/1.9781611972740.59openalex-snapshot
Privacy Preserving Naïve Bayes Classifier for Vertically Partitioned Data
inferredcites →https://doi.org/10.1137/1.9781611972764.47openalex-snapshot
A New Privacy-Preserving Distributed k-Clustering Algorithm
inferredcites →https://doi.org/10.1145/1014052.1014126openalex-snapshot
When do data mining results violate privacy?
inferredcites →https://doi.org/10.1145/1014052.1014145openalex-snapshot
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data
inferredcites →https://doi.org/10.1145/1081870.1081942openalex-snapshot
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
inferredcites →https://doi.org/10.1145/375551.375602openalex-snapshot
On the design and quantification of privacy preserving data mining algorithms
inferredcites →https://doi.org/10.1145/383962.384047openalex-snapshot
Selective private function evaluation with applications to private statistics
inferredcites →https://doi.org/10.1145/775047.775080openalex-snapshot
Privacy preserving mining of association rules
inferredcites →https://doi.org/10.1145/775047.775142openalex-snapshot
Privacy preserving association rule mining in vertically partitioned data
inferredcites →https://doi.org/10.1145/775079.775080openalex-snapshot
Privacy preserving mining of association rules
inferredcites →https://doi.org/10.1145/872757.872771openalex-snapshot
Information sharing across private databases
inferredcites →https://doi.org/10.1145/956750.956776openalex-snapshot
Privacy-preserving k -means clustering over vertically partitioned data
inferredcites →https://doi.org/10.5040/9781472559500.0016openalex-snapshot
Directive 97/66/EC of the European Parliament and of the Council of 15 December 1997 concerning the processing of personal data and the protection of privacy in the telecommunications sector
inferredcites →https://doi.org/10.5040/9781509967339.v2_0037openalex-snapshot
Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/11801412_7openalex-snapshot
Distributed Data Mining Protocols for Privacy: A Review of Some Recent Results
inferred← citeshttps://doi.org/10.1007/978-3-030-60248-2_42openalex-snapshot
DOS-GAN: A Distributed Over-Sampling Method Based on Generative Adversarial Networks for Distributed Class-Imbalance Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-09153-2_52openalex-snapshot
Privacy-Preserving Kriging Interpolation on Distributed Data
inferred← citeshttps://doi.org/10.1007/978-3-540-78478-4_8openalex-snapshot
Towards Privacy-Preserving Model Selection
inferred← citeshttps://doi.org/10.1007/978-3-642-03549-4_3openalex-snapshot
Privacy-Preserving Information Markets for Computing Statistical Data
inferred← citeshttps://doi.org/10.1007/978-3-642-16949-6_13openalex-snapshot
A Distributed and Privacy-Preserving Method for Network Intrusion Detection
inferred← citeshttps://doi.org/10.1007/978-3-642-17316-5_36openalex-snapshot
Efficient Privacy-Preserving Data Mining in Malicious Model
inferred← citeshttps://doi.org/10.1007/978-3-642-17316-5_41openalex-snapshot
Privacy-Preserving Data Mining in Presence of Covert Adversaries
inferred← citeshttps://doi.org/10.1007/978-3-642-30487-3_11openalex-snapshot
Privacy-Preserving Data Mining Techniques: Survey and Challenges
inferred← citeshttps://doi.org/10.1007/s40747-024-01424-0openalex-snapshot
VertiBayes: learning Bayesian network parameters from vertically partitioned data with missing values
inferred← citeshttps://doi.org/10.1016/j.asoc.2013.03.011openalex-snapshot
Incremental learning of privacy-preserving Bayesian networks
inferred← citeshttps://doi.org/10.1016/j.asoc.2021.107819openalex-snapshot
Securing private information by data perturbation using statistical transformation with three dimensional shearing
inferred← citeshttps://doi.org/10.1016/j.comnet.2018.07.009openalex-snapshot
A Bayesian network model for data losses and faults in medical body sensor networks
inferred← citeshttps://doi.org/10.1016/j.datak.2009.04.006openalex-snapshot
Impossibility of unconditionally secure scalar products
inferred← citeshttps://doi.org/10.1016/j.dcan.2020.09.001openalex-snapshot
Security and privacy issues of physical objects in the IoT: Challenges and opportunities
inferred← citeshttps://doi.org/10.1016/j.jksuci.2016.11.009openalex-snapshot
Privacy preserving data mining with 3-D rotation transformation
inferred← citeshttps://doi.org/10.1016/j.jksuci.2020.06.010openalex-snapshot
A hybrid-security model for privacy-enhanced distributed data mining
inferred← citeshttps://doi.org/10.1016/j.knosys.2015.10.025openalex-snapshot
Rough sets in distributed decision information systems
inferred← citeshttps://doi.org/10.1016/j.neucom.2014.05.078openalex-snapshot
Weighted ensemble learning of Bayesian network for gene regulatory networks
inferred← citeshttps://doi.org/10.1109/cdan.2016.7570874openalex-snapshot
A survey on privacy preserving mining implementing techniques
inferred← citeshttps://doi.org/10.1109/cisda.2009.5356544openalex-snapshot
Secure two and multi-party association rule mining
inferred← citeshttps://doi.org/10.1109/comst.2023.3330910openalex-snapshot
Federated Learning and Meta Learning: Approaches, Applications, and Directions
inferred← citeshttps://doi.org/10.1109/cse.2009.94openalex-snapshot
Privacy-Preserving Bayesian Network for Horizontally Partitioned Data
inferred← citeshttps://doi.org/10.1109/hpcc/smartcity/dss.2019.00049openalex-snapshot
A Distributed Class-Incremental Learning Method Based on Neural Network Parameter Fusion
inferred← citeshttps://doi.org/10.1109/icaccct.2012.6320768openalex-snapshot
Privacy preserving associative classification on vertically partitioned databases
inferred← citeshttps://doi.org/10.1109/icdmw.2007.77openalex-snapshot
Experimental Comparison of Feature Subset Selection Methods
inferred← citeshttps://doi.org/10.1109/icdmw.2007.86openalex-snapshot
Privacy-Preserving Data Mining Applications in the Malicious Model
inferred← citeshttps://doi.org/10.1109/icoac.2013.6921921openalex-snapshot
Data Anonymization Using Augmented Rotation of Sub-Clusters for privacy preservation in data mining
inferred← citeshttps://doi.org/10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00115openalex-snapshot
DCIGAN: A Distributed Class-Incremental Learning Method Based on Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1109/jsyst.2016.2600582openalex-snapshot
Threshold Tuning-Based Wearable Sensor Fault Detection for Reliable Medical Monitoring Using Bayesian Network Model
inferred← citeshttps://doi.org/10.1109/smart46866.2019.9117391openalex-snapshot
Privacy Preserving Classification using 4-Dimensional Rotation Transformation
inferred← citeshttps://doi.org/10.1109/tie.2021.3076710openalex-snapshot
Autonomous Decision-Making of Welding Position During Multipass GMAW With T-Joints: A Bayesian Network Approach
inferred← citeshttps://doi.org/10.1109/tkde.2018.2880743openalex-snapshot
DAG: A General Model for Privacy-Preserving Data Mining
inferred← citeshttps://doi.org/10.1109/tmc.2025.3609202openalex-snapshot
A Privacy-Preserving Auction for Task Offloading and Resource Allocation in UAV-Assisted MEC
inferred← citeshttps://doi.org/10.1109/tsp.2010.2088393openalex-snapshot
Attribute-Distributed Learning: Models, Limits, and Algorithms
inferred← citeshttps://doi.org/10.1142/s0219622010003919openalex-snapshot
PRIVACY-PRESERVING SVD-BASED COLLABORATIVE FILTERING ON PARTITIONED DATA
inferred← citeshttps://doi.org/10.1142/s0219622013500090openalex-snapshot
PRIVACY-PRESERVING RANDOM PROJECTION-BASED RECOMMENDATIONS BASED ON DISTRIBUTED DATA
inferred← citeshttps://doi.org/10.1145/2001858.2002103openalex-snapshot
Privacy-preserving approach to bayesian network structure learning from distributed data
inferred← citeshttps://doi.org/10.12785/amis/080245openalex-snapshot
An Information Security Threat Assessment Model based on Bayesian Network and OWA Operator
inferred← citeshttps://doi.org/10.12948/issn14531305/17.3.2013.14openalex-snapshot
Security Solutions for Privacy Preserving Improved Data Mining
inferred← citeshttps://doi.org/10.1371/annotation/4bf3c893-ad02-4730-b775-fd83fd8d174copenalex-snapshot
Correction: Using Consensus Bayesian Network to Model the Reactive Oxygen Species Regulatory Pathway
inferred← citeshttps://doi.org/10.1371/journal.pone.0056832openalex-snapshot
Using Consensus Bayesian Network to Model the Reactive Oxygen Species Regulatory Pathway
inferred← citeshttps://doi.org/10.1504/ijics.2008.022488openalex-snapshot
Privacy-preserving data mining in the malicious model
inferred← citeshttps://doi.org/10.17485/ijst/2016/v9i47/108078openalex-snapshot
An Inception of DDoS Attacks for Popular Websites - Identifying on Application-Layer
inferred← citeshttps://doi.org/10.21203/rs.3.rs-330469/v1openalex-snapshot
Stable 3D seam tracking for thick plate GMAW manufacturing with T-joints using Kalman filter and machine learning
inferred← citeshttps://doi.org/10.21608/jesaun.2013.114882openalex-snapshot
PRIVACY-PRESERVING DATA MINING OF DISTRIBUTED DATABASES USING NAÏVE BAYES CLASSIFIER
inferred← citeshttps://doi.org/10.28991/esj-2022-06-06-014openalex-snapshot
Data Mining Applications in Banking Sector While Preserving Customer Privacy
inferred← citeshttps://doi.org/10.3233/jcs-2010-0417openalex-snapshot
Secure construction and publication of contingency tables from distributed data
inferred← citeshttps://doi.org/10.3390/math14152669openalex-snapshot
Applied Bayesian Networks Rely on Expert Knowledge and Scarce Data Sharing
inferred← citeshttps://doi.org/10.3923/itj.2010.1.10openalex-snapshot
A Privacy Preserving Neural Network Learning Algorithm for Horizontally Partitioned Databases
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amm.596.119openalex-snapshot
Study on the Transformation of Military Logistical of Internet of Things Era
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amm.713-715.1863openalex-snapshot
Research on Privacy Preserving Classification Algorithm
inferred← citeshttps://doi.org/10.4208/jics.v8.n2.p119openalex-snapshot
Privacy Preserving Three-Layer Naïve Bayes Classifier for Vertically Partitioned Databases
inferred← citeshttps://doi.org/10.48550/arxiv.1206.2038openalex-snapshot
CloudMine: Multi-Party Privacy-Preserving Data Analytics Service
inferred← citeshttps://doi.org/10.48550/arxiv.1304.6575openalex-snapshot
Third Party Privacy Preserving Protocol for Perturbation Based Classification of Vertically Fragmented Data Bases
inferred← citeshttps://doi.org/10.48550/arxiv.2110.09356openalex-snapshot
Towards Federated Bayesian Network Structure Learning with Continuous Optimization
inferred← citeshttps://doi.org/10.5120/10639-5392openalex-snapshot
SMC Protocol for Naïve Bayes Classification over Grid Partitioned Data using Multiple UTPs
inferred← citeshttps://doi.org/10.5120/14099-2118openalex-snapshot
Third Party Privacy Preserving Protocol for Secure Web Services
inferred← citeshttps://doi.org/10.5120/16347-5687openalex-snapshot
Privacy Preserving Data Mining Techniques in a Distributed Environment
inferred← citeshttps://doi.org/10.5120/cae2015651825openalex-snapshot
C Privacy Prevention of Discriminating Rules by Perturbing Sensitive Items
inferred← citeshttps://doi.org/10.5555/1747335.1747336openalex-snapshot
Communication-Efficient Privacy-Preserving Clustering
inferred← citeshttps://doi.org/10.70675/851ea73az7fedz485fza157z6aa9de5418fcopenalex-snapshot
Apprentissage fédéré de réseaux bayésiens préservant la confidentialité dans le cadre d’applications médicales personnalisées
inferred← citeshttps://doi.org/10.7282/t34t6hhtopenalex-snapshot
Privacy preserving analysis of graph structured data
inferred← citeshttps://doi.org/10.9790/0661-0760412openalex-snapshot
Privacy Preserving Naïve Bayes Classifier for Horizontally Distribution Scenario Using Un-trusted Third Party
inferred← citeshttps://doi.org/10.9790/0661-145112119openalex-snapshot
Multilevel Privacy Preserving by Linear and Non Linear Data Distortion
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.