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K-Anonymity through the Enhanced Clustering Method

https://doi.org/10.1109/icebe.2016.024
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What this work says

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

inferredcites →https://doi.org/10.1007/11823728_39openalex-snapshot
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
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/s00145-001-0019-2openalex-snapshot
Privacy Preserving Data Mining
inferredcites →https://doi.org/10.1016/b978-155860869-6/50066-4openalex-snapshot
Maintaining Data Privacy in Association Rule Mining
inferredcites →https://doi.org/10.1080/01621459.1980.10477481openalex-snapshot
Suppression Methodology and Statistical Disclosure Control
inferredcites →https://doi.org/10.1109/69.971193openalex-snapshot
Protecting respondents identities in microdata release
inferredcites →https://doi.org/10.1109/icde.2005.143openalex-snapshot
Top-Down Specialization for Information and Privacy Preservation
inferredcites →https://doi.org/10.1109/icdm.2004.10110openalex-snapshot
Bottom-Up Generalization: A Data Mining Solution to Privacy Protection
inferredcites →https://doi.org/10.1109/tkde.2008.129openalex-snapshot
k-Anonymization with Minimal Loss of Information
inferredcites →https://doi.org/10.1142/s0218488502001648openalex-snapshot
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
inferredcites →https://doi.org/10.1145/1014052.1014145openalex-snapshot
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data
inferredcites →https://doi.org/10.1145/1055558.1055591openalex-snapshot
On the complexity of optimal K-anonymity
inferredcites →https://doi.org/10.1145/1066157.1066164openalex-snapshot
Incognito
inferredcites →https://doi.org/10.1145/1081870.1081942openalex-snapshot
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
inferredcites →https://doi.org/10.1145/1142351.1142374openalex-snapshot
Achieving anonymity via clustering
inferredcites →https://doi.org/10.1145/1150402.1150504openalex-snapshot
Utility-based anonymization using local recoding
inferredcites →https://doi.org/10.1145/1798596.1798602openalex-snapshot
Achieving anonymity via clustering
inferredcites →https://doi.org/10.1145/335191.335438openalex-snapshot
Privacy-preserving data mining
inferredcites →https://doi.org/10.1145/375551.375602openalex-snapshot
On the design and quantification of privacy preserving data mining algorithms
inferredcites →https://doi.org/10.1145/775047.775089openalex-snapshot
Transforming data to satisfy privacy constraints
inferredcites →https://doi.org/10.1145/956750.956776openalex-snapshot
Privacy-preserving k -means clustering over vertically partitioned data
inferredcites →https://doi.org/10.1145/956755.956776openalex-snapshot
Privacy-preserving k-means clustering over vertically partitioned data
inferredcites →https://doi.org/10.1184/r1/6625469openalex-snapshot
Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression
inferredcites →https://doi.org/10.2307/1229519openalex-snapshot
The Death of Privacy?

What points at this work

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

inferred← citeshttps://doi.org/10.1002/spy2.13openalex-snapshot
Challenges and techniques in Big data security and privacy: A review
inferred← citeshttps://doi.org/10.1007/978-3-030-36938-5_37openalex-snapshot
Privacy-Preserving Sequential Data Publishing
inferred← citeshttps://doi.org/10.1007/978-981-19-4044-6_4openalex-snapshot
Black Hole Algorithm for BigData Anonymization
inferred← citeshttps://doi.org/10.1007/s10586-017-1108-9openalex-snapshot
An evolutionary feature set decomposition based anonymization for classification workloads: Privacy Preserving Data Mining
inferred← citeshttps://doi.org/10.1007/s11227-022-04517-0openalex-snapshot
Protection of data privacy from vulnerability using two-fish technique with Apriori algorithm in data mining
inferred← citeshttps://doi.org/10.1007/s13369-019-03999-0openalex-snapshot
Adaptive k-Anonymity Approach for Privacy Preserving in Cloud
inferred← citeshttps://doi.org/10.1016/j.jksuci.2021.04.014openalex-snapshot
KAB: A new k-anonymity approach based on black hole algorithm
inferred← citeshttps://doi.org/10.1016/j.procs.2018.01.097openalex-snapshot
A new technique ensuring privacy in big data: K -anonymity without prior value of the threshold k
inferred← citeshttps://doi.org/10.1109/cse-euc.2017.197openalex-snapshot
Towards Location and Trajectory Privacy Preservation in 5G Vehicular Social Network
inferred← citeshttps://doi.org/10.1109/etcce54784.2021.9689791openalex-snapshot
A Conceptual Anonymity Model to Ensure Privacy for Sensitive Network Data
inferred← citeshttps://doi.org/10.1109/etcce54784.2021.9689872openalex-snapshot
A Conceptual Anonymity Model to Ensure Privacy for Sensitive Network Data
inferred← citeshttps://doi.org/10.1109/icitech.2017.8080053openalex-snapshot
Attribute based diversity model for privacy preservation
inferred← citeshttps://doi.org/10.1145/3318299.3318389openalex-snapshot
Feature Based Data Anonymization with Slicing Method for Data Publishing
inferred← citeshttps://doi.org/10.1145/3349341.3349376openalex-snapshot
Role-Based Static Desensitization Protection Method for Privacy Data
inferred← citeshttps://doi.org/10.1145/3608482openalex-snapshot
The Privacy Issue of Counterfactual Explanations: Explanation Linkage Attacks
inferred← citeshttps://doi.org/10.1145/3664476.3669916openalex-snapshot
Advanced methods for generalizing time and duration during dataset anonymization
inferred← citeshttps://doi.org/10.3233/kes-190415openalex-snapshot
Fine-grained k-anonymity for privacy preserving in cloud
inferred← citeshttps://doi.org/10.32604/cmc.2020.09667openalex-snapshot
δ-calculus: A New Approach to Quantifying Location Privacy☆
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