Fuzzy k-anonymity with uncertainty parameter φ anonymizes 64% of unique nodes on average at 5% uncertainty across 39 networks and over 99% with a new Greedy algorithm at 10% uncertainty under 5% edge budget, while keeping structural metrics within 5% change.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.SI 2representative citing papers
Introduces a unified framework with full, partial and budgeted anonymization variants plus four heuristics that outperform baselines by retaining more edges and producing more anonymous nodes.
citing papers explorer
-
Fuzzy k-anonymity in complex networks
Fuzzy k-anonymity with uncertainty parameter φ anonymizes 64% of unique nodes on average at 5% uncertainty across 39 networks and over 99% with a new Greedy algorithm at 10% uncertainty under 5% edge budget, while keeping structural metrics within 5% change.
-
The anonymization problem in social networks
Introduces a unified framework with full, partial and budgeted anonymization variants plus four heuristics that outperform baselines by retaining more edges and producing more anonymous nodes.