k-Anonymity on Graphs Using the Szemerédi Regularity Lemma

Graph anonymization aims at reducing the ability of an attacker to identify nodes a graph by obfuscating its structural information. In k-anonymity, this means making each node indistinguishable from least other k-1 nodes. Simply stripping their identifying label is insufficient, as with enough knowledge can still recover identities. We propose algorithm enforce k-anonymity based on Szemerédi regularity lemma. Given graph, we start computing regular partition The lemma ensures that such exists and edges between sets behave quasi-randomly. With hand, anonymize randomizing within set, obtaining structurally similar original one yet set are indistinguishable. Unlike k-anonymization methods, our approach does not consider single type attack, but instead it prevent any structure-based de-anonymization attempt. test framework wide range real-world networks compare against another simple widely used technique demonstrating effectiveness approach.